Demand and generation cost uncertainty modelling in power system optimization studies
Energy Technology Data Exchange (ETDEWEB)
Gomes, Bruno Andre; Saraiva, Joao Tome [INESC Porto and Departamento de Engenharia Electrotecnica e Computadores, Faculdade de Engenharia da Universidade do Porto, FEUP, Campus da FEUP Rua Roberto Frias 378, 4200 465 Porto (Portugal)
2009-06-15
This paper describes the formulations and the solution algorithms developed to include uncertainties in the generation cost function and in the demand on DC OPF studies. The uncertainties are modelled by trapezoidal fuzzy numbers and the solution algorithms are based on multiparametric linear programming techniques. These models are a development of an initial formulation detailed in several publications co-authored by the second author of this paper. Now, we developed a more complete model and a more accurate solution algorithm in the sense that it is now possible to capture the widest possible range of values of the output variables reflecting both demand and generation cost uncertainties. On the other hand, when modelling simultaneously demand and generation cost uncertainties, we are representing in a more realistic way the volatility that is currently inherent to power systems. Finally, the paper includes a case study to illustrate the application of these models based on the IEEE 24 bus test system. (author)
SunShot solar power reduces costs and uncertainty in future low-carbon electricity systems.
Mileva, Ana; Nelson, James H; Johnston, Josiah; Kammen, Daniel M
2013-08-20
The United States Department of Energy's SunShot Initiative has set cost-reduction targets of $1/watt for central-station solar technologies. We use SWITCH, a high-resolution electricity system planning model, to study the implications of achieving these targets for technology deployment and electricity costs in western North America, focusing on scenarios limiting carbon emissions to 80% below 1990 levels by 2050. We find that achieving the SunShot target for solar photovoltaics would allow this technology to provide more than a third of electric power in the region, displacing natural gas in the medium term and reducing the need for nuclear and carbon capture and sequestration (CCS) technologies, which face technological and cost uncertainties, by 2050. We demonstrate that a diverse portfolio of technological options can help integrate high levels of solar generation successfully and cost-effectively. The deployment of GW-scale storage plays a central role in facilitating solar deployment and the availability of flexible loads could increase the solar penetration level further. In the scenarios investigated, achieving the SunShot target can substantially mitigate the cost of implementing a carbon cap, decreasing power costs by up to 14% and saving up to $20 billion ($2010) annually by 2050 relative to scenarios with Reference solar costs.
Joint cost of energy under an optimal economic policy of hybrid power systems subject to uncertainty
International Nuclear Information System (INIS)
Díaz, Guzmán; Planas, Estefanía; Andreu, Jon; Kortabarria, Iñigo
2015-01-01
Economical optimization of hybrid systems is usually performed by means of LCoE (levelized cost of energy) calculation. Previous works deal with the LCoE calculation of the whole hybrid system disregarding an important issue: the stochastic component of the system units must be jointly considered. This paper deals with this issue and proposes a new fast optimal policy that properly calculates the LCoE of a hybrid system and finds the lowest LCoE. This proposed policy also considers the implied competition among power sources when variability of gas and electricity prices are taken into account. Additionally, it presents a comparative between the LCoE of the hybrid system and its individual technologies of generation by means of a fast and robust algorithm based on vector logical computation. Numerical case analyses based on realistic data are presented that valuate the contribution of technologies in a hybrid power system to the joint LCoE. - Highlights: • We perform the LCoE calculation with the stochastic component jointly considered. • We propose a fast an optimal policy that minimizes the LCoE. • We compare the obtained LCoEs by means of a fast and robust algorithm. • We take into account the competition among gas prices and electricity prices
Nuclear costs: indicators and uncertainties
International Nuclear Information System (INIS)
Leveque, Francois
2013-01-01
In order to identify whether it is better to build a gas plant, a nuclear plant or a wind farm, to identify the technology leading to the lowest KWh cost, to identify under which conditions nuclear production is profitable for a private investor, and to identify whether taking the dismantling cost and the waste storage cost into account modifies the nuclear competitiveness with respect to general interest, the author first discusses the different costs of the nuclear sector, their sensitivity to different factors. In a second part, he proposes a retrospective discussion of cost dynamics. Then, as nuclear technology seems characterized by always increasing costs, and as this trend may last, notably because of safety concerns, the author proposes an analysis of the poor competitiveness of nuclear with respect to its cost
Low cost high performance uncertainty quantification
Bekas, C.; Curioni, A.; Fedulova, I.
2009-01-01
Uncertainty quantification in risk analysis has become a key application. In this context, computing the diagonal of inverse covariance matrices is of paramount importance. Standard techniques, that employ matrix factorizations, incur a cubic cost
Uncertainty in relative cost investigation
International Nuclear Information System (INIS)
Bunn, D.; Viahos, K.
1989-01-01
One of the consequences of the privatization of the Central Electricity Generating Board has been a weakening of the economic case for nuclear generation over coal. Nuclear has higher capital, but lower operating costs than coal and is therefore favoured in capital budgeting by discounting at lower rates of return. In the Sizewell case (in 1987), discounting at the public sector rate of 5 per cent favoured nuclear. However, the private sector will require higher rates of return, thus rendering nuclear less attractive. Hence the imposition by the government of a diversity constraint on the privatized industry to ensure that contracts are made for a minimum fraction of non-fossil (essentially nuclear) energy. An electricity capacity planning model was developed to estimate the costs of imposing various non-fossil energy constraints on the planning decision of a privatized electricity supply industry, as a function of various discount rates. Using a large-scale linear programming technique, the model optimizes over a 50 year horizon the schedule of installation, and mix of generating capacity, both with and without a minimum non-fossil constraint. The conclusion is that the opportunity cost of diversity may be a complex joint substation of more than one type of plant (eg coal and gas) depending on the discount rate. (author)
Low cost high performance uncertainty quantification
Bekas, C.
2009-01-01
Uncertainty quantification in risk analysis has become a key application. In this context, computing the diagonal of inverse covariance matrices is of paramount importance. Standard techniques, that employ matrix factorizations, incur a cubic cost which quickly becomes intractable with the current explosion of data sizes. In this work we reduce this complexity to quadratic with the synergy of two algorithms that gracefully complement each other and lead to a radically different approach. First, we turned to stochastic estimation of the diagonal. This allowed us to cast the problem as a linear system with a relatively small number of multiple right hand sides. Second, for this linear system we developed a novel, mixed precision, iterative refinement scheme, which uses iterative solvers instead of matrix factorizations. We demonstrate that the new framework not only achieves the much needed quadratic cost but in addition offers excellent opportunities for scaling at massively parallel environments. We based our implementation on BLAS 3 kernels that ensure very high processor performance. We achieved a peak performance of 730 TFlops on 72 BG/P racks, with a sustained performance 73% of theoretical peak. We stress that the techniques presented in this work are quite general and applicable to several other important applications. Copyright © 2009 ACM.
International Nuclear Information System (INIS)
Nie, S.; Li, Y.P.; Liu, J.; Huang, Charley Z.
2017-01-01
An interval-stochastic risk management (ISRM) method is launched to control the variability of the recourse cost as well as to capture the notion of risk in stochastic programming. The ISRM method can examine various policy scenarios that are associated with economic penalties under uncertainties presented as probability distributions and interval values. An ISRM model is then formulated to identify the optimal power mix for the Beijing's energy system. Tradeoffs between risk and cost are evaluated, indicating any change in targeted cost and risk level would yield different expected costs. Results reveal that the inherent uncertainty of system components and risk attitude of decision makers have significant effects on the city's energy-supply and electricity-generation schemes as well as system cost and probabilistic penalty. Results also disclose that import electricity as a recourse action to compensate the local shortage would be enforced. The import electricity would increase with a reduced risk level; under every risk level, more electricity would be imported with an increased demand. The findings can facilitate the local authority in identifying desired strategies for the city's energy planning and management in association with financial-cost minimization and environmental-impact mitigation. - Highlights: • Interval-stochastic risk management method is launched to identify optimal power mix. • It is advantageous in capturing the notion of risk in stochastic programming. • Results reveal that risk attitudes can affect optimal power mix and financial cost. • Developing renewable energies would enhance the sustainability of energy management. • Import electricity as an action to compensate the local shortage would be enforced.
Directory of Open Access Journals (Sweden)
Sheridan Few
2017-01-01
Full Text Available There exists considerable uncertainty over both shale and conventional gas resource availability and extraction costs, as well as the fugitive methane emissions associated with shale gas extraction and its possible role in mitigating climate change. This study uses a multi-region energy system model, TIAM (TIMES integrated assessment model, to consider the impact of a range of conventional and shale gas cost and availability assessments on mitigation scenarios aimed at achieving a limit to global warming of below 2 °C in 2100, with a 50% likelihood. When adding shale gas to the global energy mix, the reduction to the global energy system cost is relatively small (up to 0.4%, and the mitigation cost increases by 1%–3% under all cost assumptions. The impact of a “dash for shale gas”, of unavailability of carbon capture and storage, of increased barriers to investment in low carbon technologies, and of higher than expected leakage rates, are also considered; and are each found to have the potential to increase the cost and reduce feasibility of meeting global temperature goals. We conclude that the extraction of shale gas is not likely to significantly reduce the effort required to mitigate climate change under globally coordinated action, but could increase required mitigation effort if not handled sufficiently carefully.
Robust guaranteed cost tracking control of quadrotor UAV with uncertainties.
Xu, Zhiwei; Nian, Xiaohong; Wang, Haibo; Chen, Yinsheng
2017-07-01
In this paper, a robust guaranteed cost controller (RGCC) is proposed for quadrotor UAV system with uncertainties to address set-point tracking problem. A sufficient condition of the existence for RGCC is derived by Lyapunov stability theorem. The designed RGCC not only guarantees the whole closed-loop system asymptotically stable but also makes the quadratic performance level built for the closed-loop system have an upper bound irrespective to all admissible parameter uncertainties. Then, an optimal robust guaranteed cost controller is developed to minimize the upper bound of performance level. Simulation results verify the presented control algorithms possess small overshoot and short setting time, with which the quadrotor has ability to perform set-point tracking task well. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Cost uncertainty for different levels of technology maturity
International Nuclear Information System (INIS)
DeMuth, S.F.; Franklin, A.L.
1996-01-01
It is difficult at best to apply a single methodology for estimating cost uncertainties related to technologies of differing maturity. While highly mature technologies may have significant performance and manufacturing cost data available, less well developed technologies may be defined in only conceptual terms. Regardless of the degree of technical maturity, often a cost estimate relating to application of the technology may be required to justify continued funding for development. Yet, a cost estimate without its associated uncertainty lacks the information required to assess the economic risk. For this reason, it is important for the developer to provide some type of uncertainty along with a cost estimate. This study demonstrates how different methodologies for estimating uncertainties can be applied to cost estimates for technologies of different maturities. For a less well developed technology an uncertainty analysis of the cost estimate can be based on a sensitivity analysis; whereas, an uncertainty analysis of the cost estimate for a well developed technology can be based on an error propagation technique from classical statistics. It was decided to demonstrate these uncertainty estimation techniques with (1) an investigation of the additional cost of remediation due to beyond baseline, nearly complete, waste heel retrieval from underground storage tanks (USTs) at Hanford; and (2) the cost related to the use of crystalline silico-titanate (CST) rather than the baseline CS100 ion exchange resin for cesium separation from UST waste at Hanford
Public Perceptions of Regulatory Costs, Their Uncertainty and Interindividual Distribution.
Johnson, Branden B; Finkel, Adam M
2016-06-01
Public perceptions of both risks and regulatory costs shape rational regulatory choices. Despite decades of risk perception studies, this article is the first on regulatory cost perceptions. A survey of 744 U.S. residents probed: (1) How knowledgeable are laypeople about regulatory costs incurred to reduce risks? (2) Do laypeople see official estimates of cost and benefit (lives saved) as accurate? (3) (How) do preferences for hypothetical regulations change when mean-preserving spreads of uncertainty replace certain cost or benefit? and (4) (How) do preferences change when unequal interindividual distributions of hypothetical regulatory costs replace equal distributions? Respondents overestimated costs of regulatory compliance, while assuming agencies underestimate costs. Most assumed agency estimates of benefits are accurate; a third believed both cost and benefit estimates are accurate. Cost and benefit estimates presented without uncertainty were slightly preferred to those surrounded by "narrow uncertainty" (a range of costs or lives entirely within a personally-calibrated zone without clear acceptance or rejection of tradeoffs). Certain estimates were more preferred than "wide uncertainty" (a range of agency estimates extending beyond these personal bounds, thus posing a gamble between favored and unacceptable tradeoffs), particularly for costs as opposed to benefits (but even for costs a quarter of respondents preferred wide uncertainty to certainty). Agency-acknowledged uncertainty in general elicited mixed judgments of honesty and trustworthiness. People preferred egalitarian distributions of regulatory costs, despite skewed actual cost distributions, and preferred progressive cost distributions (the rich pay a greater than proportional share) to regressive ones. Efficient and socially responsive regulations require disclosure of much more information about regulatory costs and risks. © 2016 Society for Risk Analysis.
Addressing Uncertainties in Cost Estimates for Decommissioning Nuclear Facilities
International Nuclear Information System (INIS)
Benjamin, Serge; Descures, Sylvain; Du Pasquier, Louis; Francois, Patrice; Buonarotti, Stefano; Mariotti, Giovanni; Tarakonov, Jurij; Daniska, Vladimir; Bergh, Niklas; Carroll, Simon; AaSTRoeM, Annika; Cato, Anna; De La Gardie, Fredrik; Haenggi, Hannes; Rodriguez, Jose; Laird, Alastair; Ridpath, Andy; La Guardia, Thomas; O'Sullivan, Patrick; ); Weber, Inge; )
2017-01-01
The cost estimation process of decommissioning nuclear facilities has continued to evolve in recent years, with a general trend towards demonstrating greater levels of detail in the estimate and more explicit consideration of uncertainties, the latter of which may have an impact on decommissioning project costs. The 2012 report on the International Structure for Decommissioning Costing (ISDC) of Nuclear Installations, a joint recommendation by the Nuclear Energy Agency (NEA), the International Atomic Energy Agency (IAEA) and the European Commission, proposes a standardised structure of cost items for decommissioning projects that can be used either directly for the production of cost estimates or for mapping of cost items for benchmarking purposes. The ISDC, however, provides only limited guidance on the treatment of uncertainty when preparing cost estimates. Addressing Uncertainties in Cost Estimates for Decommissioning Nuclear Facilities, prepared jointly by the NEA and IAEA, is intended to complement the ISDC, assisting cost estimators and reviewers in systematically addressing uncertainties in decommissioning cost estimates. Based on experiences gained in participating countries and projects, the report describes how uncertainty and risks can be analysed and incorporated in decommissioning cost estimates, while presenting the outcomes in a transparent manner
The cost of uncertainty in capacity expansion problems
Energy Technology Data Exchange (ETDEWEB)
Jenhung Wang [National Chung Cheng Univ., Dept. of Business Administration, Chia-Yi (Taiwan); Sparrow, F.T. [Purdue Univ., School of Industrial Engineering, West Lafayette, IN (United States)
1999-07-01
The goals of this paper are to present a two-stage programming model of the capacity expansion problem under uncertainty of demand and explore the impact of the uncertainty on cost. The model is a mixed integer nonlinear programming (MINLP) model with the consideration of uncertainty used to maximise the expected presented value of utility profits over the planning horizon, under the constraints of rate of return and reserve margin regulation. The results reveal that the uncertainty harms the profit seriously. In this paper both microeconomics and mathematical programming are used to analyse the problem. We try to observe the economic behaviour of the utility with uncertainty involved. We also investigate the influence on the cost of uncertainty of each economic parameter. (Author)
Marketable pollution permits with uncertainty and transaction costs
International Nuclear Information System (INIS)
Montero, Juan-Pablo
1998-01-01
Increasing interest in the use of marketable permits for pollution control has become evident in recent years. Concern regarding their performance still remains because empirical evidence has shown transaction costs and uncertainty to be significant in past and existing marketable permits programs. In this paper we develop theoretical and numerical models that include transaction costs and uncertainty (in trade approval) to show their effects on market performance (i.e., equilibrium price of permits and trading volume) and aggregate control costs. We also show that in the presence of transaction costs and uncertainty the initial allocation of permits may not be neutral in terms of efficiency. Furthermore, using a numerical model for a hypothetical NO x trading program in which participants have discrete control technology choices, we find that aggregate control costs and the equilibrium price of permits are sensitive to the initial allocation of permits, even for constant marginal transaction costs and certainty
Cost-effective conservation of an endangered frog under uncertainty.
Rose, Lucy E; Heard, Geoffrey W; Chee, Yung En; Wintle, Brendan A
2016-04-01
How should managers choose among conservation options when resources are scarce and there is uncertainty regarding the effectiveness of actions? Well-developed tools exist for prioritizing areas for one-time and binary actions (e.g., protect vs. not protect), but methods for prioritizing incremental or ongoing actions (such as habitat creation and maintenance) remain uncommon. We devised an approach that combines metapopulation viability and cost-effectiveness analyses to select among alternative conservation actions while accounting for uncertainty. In our study, cost-effectiveness is the ratio between the benefit of an action and its economic cost, where benefit is the change in metapopulation viability. We applied the approach to the case of the endangered growling grass frog (Litoria raniformis), which is threatened by urban development. We extended a Bayesian model to predict metapopulation viability under 9 urbanization and management scenarios and incorporated the full probability distribution of possible outcomes for each scenario into the cost-effectiveness analysis. This allowed us to discern between cost-effective alternatives that were robust to uncertainty and those with a relatively high risk of failure. We found a relatively high risk of extinction following urbanization if the only action was reservation of core habitat; habitat creation actions performed better than enhancement actions; and cost-effectiveness ranking changed depending on the consideration of uncertainty. Our results suggest that creation and maintenance of wetlands dedicated to L. raniformis is the only cost-effective action likely to result in a sufficiently low risk of extinction. To our knowledge we are the first study to use Bayesian metapopulation viability analysis to explicitly incorporate parametric and demographic uncertainty into a cost-effective evaluation of conservation actions. The approach offers guidance to decision makers aiming to achieve cost
Zhou, Xiuru; Ye, Weili; Zhang, Bing
2016-03-01
Transaction costs and uncertainty are considered to be significant obstacles in the emissions trading market, especially for including nonpoint source in water quality trading. This study develops a nonlinear programming model to simulate how uncertainty and transaction costs affect the performance of point/nonpoint source (PS/NPS) water quality trading in the Lake Tai watershed, China. The results demonstrate that PS/NPS water quality trading is a highly cost-effective instrument for emissions abatement in the Lake Tai watershed, which can save 89.33% on pollution abatement costs compared to trading only between nonpoint sources. However, uncertainty can significantly reduce the cost-effectiveness by reducing trading volume. In addition, transaction costs from bargaining and decision making raise total pollution abatement costs directly and cause the offset system to deviate from the optimal state. While proper investment in monitoring and measuring of nonpoint emissions can decrease uncertainty and save on the total abatement costs. Finally, we show that the dispersed ownership of China's farmland will bring high uncertainty and transaction costs into the PS/NPS offset system, even if the pollution abatement cost is lower than for point sources. Copyright © 2015 Elsevier Ltd. All rights reserved.
Multi-scenario modelling of uncertainty in stochastic chemical systems
International Nuclear Information System (INIS)
Evans, R. David; Ricardez-Sandoval, Luis A.
2014-01-01
Uncertainty analysis has not been well studied at the molecular scale, despite extensive knowledge of uncertainty in macroscale systems. The ability to predict the effect of uncertainty allows for robust control of small scale systems such as nanoreactors, surface reactions, and gene toggle switches. However, it is difficult to model uncertainty in such chemical systems as they are stochastic in nature, and require a large computational cost. To address this issue, a new model of uncertainty propagation in stochastic chemical systems, based on the Chemical Master Equation, is proposed in the present study. The uncertain solution is approximated by a composite state comprised of the averaged effect of samples from the uncertain parameter distributions. This model is then used to study the effect of uncertainty on an isomerization system and a two gene regulation network called a repressilator. The results of this model show that uncertainty in stochastic systems is dependent on both the uncertain distribution, and the system under investigation. -- Highlights: •A method to model uncertainty on stochastic systems was developed. •The method is based on the Chemical Master Equation. •Uncertainty in an isomerization reaction and a gene regulation network was modelled. •Effects were significant and dependent on the uncertain input and reaction system. •The model was computationally more efficient than Kinetic Monte Carlo
Fuel cycle cost uncertainty from nuclear fuel cycle comparison
International Nuclear Information System (INIS)
Li, J.; McNelis, D.; Yim, M.S.
2013-01-01
This paper examined the uncertainty in fuel cycle cost (FCC) calculation by considering both model and parameter uncertainty. Four different fuel cycle options were compared in the analysis including the once-through cycle (OT), the DUPIC cycle, the MOX cycle and a closed fuel cycle with fast reactors (FR). The model uncertainty was addressed by using three different FCC modeling approaches with and without the time value of money consideration. The relative ratios of FCC in comparison to OT did not change much by using different modeling approaches. This observation was consistent with the results of the sensitivity study for the discount rate. Two different sets of data with uncertainty range of unit costs were used to address the parameter uncertainty of the FCC calculation. The sensitivity study showed that the dominating contributor to the total variance of FCC is the uranium price. In general, the FCC of OT was found to be the lowest followed by FR, MOX, and DUPIC. But depending on the uranium price, the FR cycle was found to have lower FCC over OT. The reprocessing cost was also found to have a major impact on FCC
Planning ATES systems under uncertainty
Jaxa-Rozen, Marc; Kwakkel, Jan; Bloemendal, Martin
2015-04-01
form a complex adaptive system, for which agent-based modelling provides a useful analysis framework. This study therefore explores the interactions between endogenous ATES adoption processes and the relative performance of different planning schemes, using an agent-based adoption model coupled with a hydrologic model of the subsurface. The models are parameterized to simulate typical operating conditions for ATES systems in a dense urban area. Furthermore, uncertainties relating to planning parameters, adoption processes, and climactic conditions are explicitly considered using exploratory modelling techniques. Results are therefore presented for the performance of different planning policies over a broad range of plausible scenarios.
Relationships for Cost and Uncertainty of Decision Trees
Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail
2013-01-01
This chapter is devoted to the design of new tools for the study of decision trees. These tools are based on dynamic programming approach and need the consideration of subtables of the initial decision table. So this approach is applicable only to relatively small decision tables. The considered tools allow us to compute: 1. Theminimum cost of an approximate decision tree for a given uncertainty value and a cost function. 2. The minimum number of nodes in an exact decision tree whose depth is at most a given value. For the first tool we considered various cost functions such as: depth and average depth of a decision tree and number of nodes (and number of terminal and nonterminal nodes) of a decision tree. The uncertainty of a decision table is equal to the number of unordered pairs of rows with different decisions. The uncertainty of approximate decision tree is equal to the maximum uncertainty of a subtable corresponding to a terminal node of the tree. In addition to the algorithms for such tools we also present experimental results applied to various datasets acquired from UCI ML Repository [4]. © Springer-Verlag Berlin Heidelberg 2013.
Addressing imperfect maintenance modelling uncertainty in unavailability and cost based optimization
Energy Technology Data Exchange (ETDEWEB)
Sanchez, Ana [Department of Statistics and Operational Research, Polytechnic University of Valencia, Camino de Vera, s/n, 46071 Valencia (Spain); Carlos, Sofia [Department of Chemical and Nuclear Engineering, Polytechnic University of Valencia, Camino de Vera, s/n, 46071 Valencia (Spain); Martorell, Sebastian [Department of Chemical and Nuclear Engineering, Polytechnic University of Valencia, Camino de Vera, s/n, 46071 Valencia (Spain)], E-mail: smartore@iqn.upv.es; Villanueva, Jose F. [Department of Chemical and Nuclear Engineering, Polytechnic University of Valencia, Camino de Vera, s/n, 46071 Valencia (Spain)
2009-01-15
Optimization of testing and maintenance activities performed in the different systems of a complex industrial plant is of great interest as the plant availability and economy strongly depend on the maintenance activities planned. Traditionally, two types of models, i.e. deterministic and probabilistic, have been considered to simulate the impact of testing and maintenance activities on equipment unavailability and the cost involved. Both models present uncertainties that are often categorized as either aleatory or epistemic uncertainties. The second group applies when there is limited knowledge on the proper model to represent a problem, and/or the values associated to the model parameters, so the results of the calculation performed with them incorporate uncertainty. This paper addresses the problem of testing and maintenance optimization based on unavailability and cost criteria and considering epistemic uncertainty in the imperfect maintenance modelling. It is framed as a multiple criteria decision making problem where unavailability and cost act as uncertain and conflicting decision criteria. A tolerance interval based approach is used to address uncertainty with regard to effectiveness parameter and imperfect maintenance model embedded within a multiple-objective genetic algorithm. A case of application for a stand-by safety related system of a nuclear power plant is presented. The results obtained in this application show the importance of considering uncertainties in the modelling of imperfect maintenance, as the optimal solutions found are associated with a large uncertainty that influences the final decision making depending on, for example, if the decision maker is risk averse or risk neutral.
Addressing imperfect maintenance modelling uncertainty in unavailability and cost based optimization
International Nuclear Information System (INIS)
Sanchez, Ana; Carlos, Sofia; Martorell, Sebastian; Villanueva, Jose F.
2009-01-01
Optimization of testing and maintenance activities performed in the different systems of a complex industrial plant is of great interest as the plant availability and economy strongly depend on the maintenance activities planned. Traditionally, two types of models, i.e. deterministic and probabilistic, have been considered to simulate the impact of testing and maintenance activities on equipment unavailability and the cost involved. Both models present uncertainties that are often categorized as either aleatory or epistemic uncertainties. The second group applies when there is limited knowledge on the proper model to represent a problem, and/or the values associated to the model parameters, so the results of the calculation performed with them incorporate uncertainty. This paper addresses the problem of testing and maintenance optimization based on unavailability and cost criteria and considering epistemic uncertainty in the imperfect maintenance modelling. It is framed as a multiple criteria decision making problem where unavailability and cost act as uncertain and conflicting decision criteria. A tolerance interval based approach is used to address uncertainty with regard to effectiveness parameter and imperfect maintenance model embedded within a multiple-objective genetic algorithm. A case of application for a stand-by safety related system of a nuclear power plant is presented. The results obtained in this application show the importance of considering uncertainties in the modelling of imperfect maintenance, as the optimal solutions found are associated with a large uncertainty that influences the final decision making depending on, for example, if the decision maker is risk averse or risk neutral
The French biofuels mandates under cost uncertainty - an assessment based on robust optimization
International Nuclear Information System (INIS)
Lorne, Daphne; Tchung-Ming, Stephane
2012-01-01
This paper investigates the impact of primary energy and technology cost uncertainty on the achievement of renewable and especially biofuel policies - mandates and norms - in France by 2030. A robust optimization technique that allows to deal with uncertainty sets of high dimensionality is implemented in a TIMES-based long-term planning model of the French energy transport and electricity sectors. The energy system costs and potential benefits (GHG emissions abatements, diversification) of the French renewable mandates are assessed within this framework. The results of this systemic analysis highlight how setting norms and mandates allows to reduce the variability of CO 2 emissions reductions and supply mix diversification when the costs of technological progress and prices are uncertain. Beyond that, we discuss the usefulness of robust optimization in complement of other techniques to integrate uncertainty in large-scale energy models. (authors)
Securitization of residential solar photovoltaic assets: Costs, risks and uncertainty
International Nuclear Information System (INIS)
Alafita, T.; Pearce, J.M.
2014-01-01
Limited access to low-cost financing is an impediment to high-velocity technological diffusion and high grid penetration of solar photovoltaic (PV) technology. Securitization of solar assets provides a potential solution to this problem. This paper assesses the viability of solar asset-backed securities (ABS) as a lower cost financing mechanism and identifies policies that could facilitate implementation of securitization. First, traditional solar financing is examined to provide a baseline for cost comparisons. Next, the securitization process is modeled. The model enables identification of several junctures at which risk and uncertainty influence costs. Next, parameter values are assigned and used to generate cost estimates. Results show that, under reasonable assumptions, securitization of solar power purchase agreements (PPA) can significantly reduce project financing costs, suggesting that securitization is a viable mechanism for improving the financing of PV projects. The clear impediment to the successful launch of a solar ABS is measuring and understanding the riskiness of underlying assets. This study identifies three classes of policy intervention that lower the cost of ABS by reducing risk or by improving the measurement of risk: (i) standardization of contracts and the contracting process, (ii) improved access to contract and equipment performance data, and (iii) geographic diversification. - Highlights: • Limited access to low-cost financing is hampering penetration of solar PV. • Solar asset-backed securities (ABS) provide a low cost financing mechanism. • Results for securitization of solar leases and power purchase agreements (PPA). • Securitization can significantly reduce project financing costs. • Identifies policy intervention that lower cost of ABS by reducing risk
Schwabe, O.; Shehab, E.; Erkoyuncu, J.
2015-08-01
The lack of defensible methods for quantifying cost estimate uncertainty over the whole product life cycle of aerospace innovations such as propulsion systems or airframes poses a significant challenge to the creation of accurate and defensible cost estimates. Based on the axiomatic definition of uncertainty as the actual prediction error of the cost estimate, this paper provides a comprehensive overview of metrics used for the uncertainty quantification of cost estimates based on a literature review, an evaluation of publicly funded projects such as part of the CORDIS or Horizon 2020 programs, and an analysis of established approaches used by organizations such NASA, the U.S. Department of Defence, the ESA, and various commercial companies. The metrics are categorized based on their foundational character (foundations), their use in practice (state-of-practice), their availability for practice (state-of-art) and those suggested for future exploration (state-of-future). Insights gained were that a variety of uncertainty quantification metrics exist whose suitability depends on the volatility of available relevant information, as defined by technical and cost readiness level, and the number of whole product life cycle phases the estimate is intended to be valid for. Information volatility and number of whole product life cycle phases can hereby be considered as defining multi-dimensional probability fields admitting various uncertainty quantification metric families with identifiable thresholds for transitioning between them. The key research gaps identified were the lacking guidance grounded in theory for the selection of uncertainty quantification metrics and lacking practical alternatives to metrics based on the Central Limit Theorem. An innovative uncertainty quantification framework consisting of; a set-theory based typology, a data library, a classification system, and a corresponding input-output model are put forward to address this research gap as the basis
Stochastic Systems Uncertainty Quantification and Propagation
Grigoriu, Mircea
2012-01-01
Uncertainty is an inherent feature of both properties of physical systems and the inputs to these systems that needs to be quantified for cost effective and reliable designs. The states of these systems satisfy equations with random entries, referred to as stochastic equations, so that they are random functions of time and/or space. The solution of stochastic equations poses notable technical difficulties that are frequently circumvented by heuristic assumptions at the expense of accuracy and rigor. The main objective of Stochastic Systems is to promoting the development of accurate and efficient methods for solving stochastic equations and to foster interactions between engineers, scientists, and mathematicians. To achieve these objectives Stochastic Systems presents: · A clear and brief review of essential concepts on probability theory, random functions, stochastic calculus, Monte Carlo simulation, and functional analysis · Probabilistic models for random variables an...
International Nuclear Information System (INIS)
Boak, D.M.; Painton, L.
1995-01-01
Probabilistic forecasting techniques have been used in many risk assessment and performance assessment applications on radioactive waste disposal projects such as Yucca Mountain and the Waste Isolation Pilot Plant (WIPP). Probabilistic techniques such as Monte Carlo and Latin Hypercube sampling methods are routinely used to treat uncertainties in physical parameters important in simulating radionuclide transport in a coupled geohydrologic system and assessing the ability of that system to comply with regulatory release limits. However, the use of probabilistic techniques in the treatment of uncertainties in the cost and duration of programmatic alternatives on risk and performance assessment projects is less common. Where significant uncertainties exist and where programmatic decisions must be made despite existing uncertainties, probabilistic techniques may yield important insights into decision options, especially when used in a decision analysis framework and when properly balanced with deterministic analyses. For relatively simple evaluations, these types of probabilistic evaluations can be made using personal computer-based software
Derivative-free optimization under uncertainty applied to costly simulators
International Nuclear Information System (INIS)
Pauwels, Benoit
2016-01-01
The modeling of complex phenomena encountered in industrial issues can lead to the study of numerical simulation codes. These simulators may require extensive execution time (from hours to days), involve uncertain parameters and even be intrinsically stochastic. Importantly within the context of simulation-based optimization, the derivatives of the outputs with respect to the inputs may be inexistent, inaccessible or too costly to approximate reasonably. This thesis is organized in four chapters. The first chapter discusses the state of the art in derivative-free optimization and uncertainty modeling. The next three chapters introduce three independent - although connected - contributions to the field of derivative-free optimization in the presence of uncertainty. The second chapter addresses the emulation of costly stochastic simulation codes - stochastic in the sense simulations run with the same input parameters may lead to distinct outputs. Such was the matter of the CODESTOCH project carried out at the Summer mathematical research center on scientific computing and its applications (CEMRACS) during the summer of 2013, together with two Ph.D. students from Electricity of France (EDF) and the Atomic Energy and Alternative Energies Commission (CEA). We designed four methods to build emulators for functions whose values are probability density functions. These methods were tested on two toy functions and applied to industrial simulation codes concerned with three complex phenomena: the spatial distribution of molecules in a hydrocarbon system (IFPEN), the life cycle of large electric transformers (EDF) and the repercussions of a hypothetical accidental in a nuclear plant (CEA). Emulation was a preliminary process towards optimization in the first two cases. In the third chapter we consider the influence of inaccurate objective function evaluations on direct search - a classical derivative-free optimization method. In real settings inaccuracy may never vanish
On treatment of uncertainty in system planning
International Nuclear Information System (INIS)
Flage, R.; Aven, T.
2009-01-01
In system planning and operation considerable efforts and resources are spent to reduce uncertainties, as a part of project management, uncertainty management and safety management. The basic idea seems to be that uncertainties are purely negative and should be reduced. In this paper we challenge this way of thinking, using a common industry practice as an example. In accordance with this industry practice, three uncertainty interval categories are used: ±40% intervals for the feasibility phase, ±30% intervals for the concept development phase and ±20% intervals for the engineering phase. The problem is that such a regime could easily lead to a conservative management regime encouraging the use of existing methods and tools, as new activities and novel solutions and arrangements necessarily mean increased uncertainties. In the paper we suggest an alternative approach based on uncertainty and risk descriptions, but having no predefined uncertainty reduction structures. The approach makes use of risk assessments and economic optimisation tools such as the expected net present value, but acknowledges the need for broad risk management processes which extend beyond the analyses. Different concerns need to be balanced, including economic aspects, uncertainties and risk, and practicability
Cost benchmarking of railway projects in Europe – dealing with uncertainties in cost estimates
DEFF Research Database (Denmark)
Trabo, Inara
Past experiences in the construction of high-speed railway projects demontrate either positive or negative financial outcomes of the actual project’s budget. Usually some uncertainty value is included into initial budget calculations. Uncertainty is related to the increase of material prices...... per main cost drivers were compared and analyzed. There were observed nine railway projects, comparable to the Copenhagen-Ringsted project. The results of this comparison provided a certain overview on the cost range in different budget disciplines. The Copenhagen-Ringsted project is positioned right...
Hump-shape Uncertainty, Agency Costs and Aggregate Fluctuations
Lee, Gabriel; Kevin, Salyer; Strobel, Johannes
2016-01-01
Previously measured uncertainty shocks using the U.S. data show a hump-shape time path: Uncertainty rises for two years before its decline. Current literature on the effects uncertainty on macroeconomics, including housing, has not accounted for this observation. Consequently, the literature on uncertainty and macroeconomics is divided on the effcts and the propagation mechanism of uncertainty on aggregate uctuations. This paper shows that when uncertainty rises and falls over time, th...
US firms still restructuring, cutting costs under oil price uncertainty
International Nuclear Information System (INIS)
Koen, A.D.
1994-01-01
Despite more than a decade of downsizing, continuing uncertainty in oil markets is forcing US petroleum companies into another round of cutting and restructuring operations. Wellhead gas prices in the US, although still volatile, in the past 2 years have risen to levels adequate to allow profits for most producers in that sector. Higher gas reserves valuations have strengthened producers' overall balance sheets. But the slide in oil prices from the middle of fourth quarter 1993 until the recent upswing the past month has withered producers' financial performances and reserves values. With little prospect of significantly higher oil prices anytime soon, US companies feel they have little choice but to continue pressing cost cutting moves in order to sustain profits in the near term while at the same time earnings a higher return on investment in the long term. Petroleum company executives are overlooking almost no operating or investment strategy thought capable of bolstering the bottom line. Because no two US oil and gas companies are alike, each profit protection plan is a unique mix of similar solutions. Oil and gas production companies most often try to lower operating costs by vigorously selling noncore properties or business units and reducing staff. The paper discusses measures taken by oil and gas companies to lower costs
Starling flock networks manage uncertainty in consensus at low cost.
Directory of Open Access Journals (Sweden)
George F Young
Full Text Available Flocks of starlings exhibit a remarkable ability to maintain cohesion as a group in highly uncertain environments and with limited, noisy information. Recent work demonstrated that individual starlings within large flocks respond to a fixed number of nearest neighbors, but until now it was not understood why this number is seven. We analyze robustness to uncertainty of consensus in empirical data from multiple starling flocks and show that the flock interaction networks with six or seven neighbors optimize the trade-off between group cohesion and individual effort. We can distinguish these numbers of neighbors from fewer or greater numbers using our systems-theoretic approach to measuring robustness of interaction networks as a function of the network structure, i.e., who is sensing whom. The metric quantifies the disagreement within the network due to disturbances and noise during consensus behavior and can be evaluated over a parameterized family of hypothesized sensing strategies (here the parameter is number of neighbors. We use this approach to further show that for the range of flocks studied the optimal number of neighbors does not depend on the number of birds within a flock; rather, it depends on the shape, notably the thickness, of the flock. The results suggest that robustness to uncertainty may have been a factor in the evolution of flocking for starlings. More generally, our results elucidate the role of the interaction network on uncertainty management in collective behavior, and motivate the application of our approach to other biological networks.
Starling Flock Networks Manage Uncertainty in Consensus at Low Cost
Young, George F.; Scardovi, Luca; Cavagna, Andrea; Giardina, Irene; Leonard, Naomi E.
2013-01-01
Flocks of starlings exhibit a remarkable ability to maintain cohesion as a group in highly uncertain environments and with limited, noisy information. Recent work demonstrated that individual starlings within large flocks respond to a fixed number of nearest neighbors, but until now it was not understood why this number is seven. We analyze robustness to uncertainty of consensus in empirical data from multiple starling flocks and show that the flock interaction networks with six or seven neighbors optimize the trade-off between group cohesion and individual effort. We can distinguish these numbers of neighbors from fewer or greater numbers using our systems-theoretic approach to measuring robustness of interaction networks as a function of the network structure, i.e., who is sensing whom. The metric quantifies the disagreement within the network due to disturbances and noise during consensus behavior and can be evaluated over a parameterized family of hypothesized sensing strategies (here the parameter is number of neighbors). We use this approach to further show that for the range of flocks studied the optimal number of neighbors does not depend on the number of birds within a flock; rather, it depends on the shape, notably the thickness, of the flock. The results suggest that robustness to uncertainty may have been a factor in the evolution of flocking for starlings. More generally, our results elucidate the role of the interaction network on uncertainty management in collective behavior, and motivate the application of our approach to other biological networks. PMID:23382667
Robustness of dynamic systems with parameter uncertainties
Balemi, S; Truöl, W
1992-01-01
Robust Control is one of the fastest growing and promising areas of research today. In many practical systems there exist uncertainties which have to be considered in the analysis and design of control systems. In the last decade methods were developed for dealing with dynamic systems with unstructured uncertainties such as HOO_ and £I-optimal control. For systems with parameter uncertainties, the seminal paper of V. L. Kharitonov has triggered a large amount of very promising research. An international workshop dealing with all aspects of robust control was successfully organized by S. P. Bhattacharyya and L. H. Keel in San Antonio, Texas, USA in March 1991. We organized the second international workshop in this area in Ascona, Switzer land in April 1992. However, this second workshop was restricted to robust control of dynamic systems with parameter uncertainties with the objective to concentrate on some aspects of robust control. This book contains a collection of papers presented at the International W...
Automatic Voltage Control (AVC) System under Uncertainty from Wind Power
DEFF Research Database (Denmark)
Qin, Nan; Abildgaard, Hans; Flynn, Damian
2016-01-01
An automatic voltage control (AVC) system maintains the voltage profile of a power system in an acceptable range and minimizes the operational cost by coordinating the regulation of controllable components. Typically, all of the parameters in the optimization problem are assumed to be certain...... and constant in the decision making process. However, for high shares of wind power, uncertainty in the decision process due to wind power variability may result in an infeasible AVC solution. This paper proposes a voltage control approach which considers the voltage uncertainty from wind power productions....... The proposed method improves the performance and the robustness of a scenario based approach by estimating the potential voltage variations due to fluctuating wind power production, and introduces a voltage margin to protect the decision against uncertainty for each scenario. The effectiveness of the proposed...
Reducing prediction uncertainty of weather controlled systems
Doeswijk, T.G.
2007-01-01
In closed agricultural systems the weather acts both as a disturbance and as a resource. By using weather forecasts in control strategies the effects of disturbances can be minimized whereas the resources can be utilized. In this situation weather forecast uncertainty and model based control are
Calorimetric and reactor coolant system flow uncertainty
International Nuclear Information System (INIS)
Bates, L.; McLean, T.
1991-01-01
This paper describes a methodology for the quantification of errors associated with the determination of a feedwater flow, secondary power, and Reactor Coolant System (RCS) flow used at the Trojan Nuclear Plant to ensure compliance with regulatory requirements. The sources of error in Plant indications and process measurement are identified and tracked, using examples, through the mathematical processes necessary to calculate the uncertainty in the RCS flow measurement. An error of approximately 1.4 percent is calculated for secondary power. This error results, along with the consideration of other errors, in an uncertainty of approximately 3 percent in the RCS flow determination
International Nuclear Information System (INIS)
Grand, P.; Danby, G.; Keane, J.; Spiro, J.; Sutter, D.; Cole, F.; Hoyer, E.; Freytag, K.; Burke, R.
1978-01-01
The purpose of the meeting was to discuss and develop cost-estimating methods for heavy-ion fusion accelerator systems. The group did not consider that its purpose was to make technical judgments on proposed systems, but to develop methods for making reasonable cost estimates of these systems. Such estimates will, it is hoped, provide material for systems studies, will help in guiding research and development efforts by identifying high-leverage subsystems (areas that account for a significant part of total system cost and that might be reduced in cost by further technical development) and to begin to provide data to aid in an eventual decision on the optimum type of accelerator for heavy-ion fusion. The systems considered as examples are: (1) injection system; (2) Wideroe linac; (3) Alvarez linac; (4) induction linac; (5) superconducting accumulator ring; (6) synchrotron; (7) final rf bunching; and (8) final beam transport to target
Sensitivity of LWR fuel cycle costs to uncertainties in detailed thermal cross sections
International Nuclear Information System (INIS)
Ryskamp, J.M.; Becker, M.; Harris, D.R.
1979-01-01
Cross sections averaged over the thermal energy (< 1 or 2 eV) group have been shown to have an important economic role for light-water reactors. Cost implications of thermal cross section uncertainties at the few-group level were reported earlier. When it has been determined that costs are sensitive to a specific thermal-group cross section, it becomes desirable to determine how specific energy-dependent cross sections influence fuel cycle costs. Multigroup cross-section sensitivity coefficients vary with fuel exposure. By changing the shape of a cross section displayed on a view-tube through an interactive graphics system, one can compute the change in few-group cross section using the exposure dependent sensitivity coefficients. With the changed exposure dependent few-group cross section, a new fuel cycle cost is computed by a sequence of batch depletion, core analysis, and fuel batch cost code modules. Fuel cycle costs are generally most sensitive to cross section uncertainties near the peak of the hardened Maxwellian flux
Uncertainty analysis in raw material and utility cost of biorefinery synthesis and design
DEFF Research Database (Denmark)
Cheali, Peam; Quaglia, Alberto; Gernaey, Krist
2014-01-01
are characterized by considerable uncertainty. These uncertainties might have significant impact on the results of the design problem, and therefore need to be carefully evaluated and managed, in order to generate candidates for robust design. In this contribution, we study the effect of data uncertainty (raw...... material price and utility cost) on the design of a biorefinery process network....
Ettema, D.F.; Timmermans, H.J.P.
2006-01-01
A negative effect of congestion that tends to be overlooked is travel time uncertainty. Travel time uncertainty causes scheduling costs due to early or late arrival. The negative effects of travel time uncertainty can be reduced by providing travellers with travel time information, which improves
International Nuclear Information System (INIS)
Grand, P.; Danby, G.; Keane, J.; Spiro, J.; Sutter, D.; Cole, F.; Hoyer, E.; Freytag, K.; Burke, R.
1977-01-01
The purpose of the meeting was to discuss and develop cost-estimating methods for heavy-ion fusion accelerator systems. The group did not consider that its purpose was to make technical judgements on proposed systems, but to develop methods for making reasonable cost estimates of these systems. Such estimates will, it is hoped, provide material for systems studies, will help in guiding research and development efforts by identifying ''high-leverage'' subsystems (areas that account for a significant part of total system cost and that might be reduced in cost by further technical development) and to begin to provide data to aid in an eventual decision on the optimum type of accelerator for heavy-ion fusion
Economic performance optimization of an absorption cooling system under uncertainty
International Nuclear Information System (INIS)
Gebreslassie, Berhane H.; Guillen-Gosalbez, Gonzalo; Jimenez, Laureano; Boer, Dieter
2009-01-01
Many of the strategies devised so far to address the optimization of energy systems are deterministic approaches that rely on estimated data. However, in real world applications there are many sources of uncertainty that introduce variability into the decision-making problem. Within this general context, we propose a novel approach to address the design of absorption cooling systems under uncertainty in the energy cost. As opposed to other approaches that optimize the expected performance of the system as a single objective, in our method the design task is formulated as a stochastic bi-criteria non-linear optimization problem that simultaneously accounts for the minimization of the expected total cost and the financial risk associated with the investment. The latter criterion is measured by the downside risk, which avoids the need to define binary variables thus improving the computational performance of the model. The capabilities of the proposed modeling framework and solution strategy are illustrated in a case study problem that addresses the design of a typical absorption cooling system. Numerical results demonstrate that the method presented allows to manage the risk level effectively by varying the area of the heat exchangers of the absorption cycle. Specifically, our strategy allows identifying the optimal values of the operating and design variables of the cycle that make it less sensitive to fluctuations in the energy price, thus improving its robustness in the face of uncertainty.
Evaluation of advanced coal gasification combined-cycle systems under uncertainty
International Nuclear Information System (INIS)
Frey, H.C.; Rubin, E.S.
1992-01-01
Advanced integrated gasification combined cycle (IGCC) systems have not been commercially demonstrated, and uncertainties remain regarding their commercial-scale performance and cost. Therefore, a probabilistic evaluation method has been developed and applied to explicitly consider these uncertainties. The insights afforded by this method are illustrated for an IGCC design featuring a fixed-bed gasifier and a hot gas cleanup system. Detailed case studies are conducted to characterize uncertainties in key measures of process performance and cost, evaluate design trade-offs under uncertainty, identify research priorities, evaluate the potential benefits of additional research, compare results for different uncertainty assumptions, and compare the advanced IGCC system to a conventional system under uncertainty. The implications of probabilistic results for research planning and technology selection are discussed in this paper
International Nuclear Information System (INIS)
Sadeghi, Mehdi; Mirshojaeian Hosseini, Hossein
2006-01-01
For many years, energy models have been used in developed or developing countries to satisfy different needs in energy planning. One of major problems against energy planning and consequently energy models is uncertainty, spread in different economic, political and legal dimensions of energy planning. Confronting uncertainty, energy planners have often used two well-known strategies. The first strategy is stochastic programming, in which energy system planners define different scenarios and apply an explicit probability of occurrence to each scenario. The second strategy is Minimax Regret strategy that minimizes regrets of different decisions made in energy planning. Although these strategies have been used extensively, they could not flexibly and effectively deal with the uncertainties caused by fuzziness. 'Fuzzy Linear Programming (FLP)' is a strategy that can take fuzziness into account. This paper tries to demonstrate the method of application of FLP for optimization of supply energy system in Iran, as a case study. The used FLP model comprises fuzzy coefficients for investment costs. Following the mentioned purpose, it is realized that FLP is an easy and flexible approach that can be a serious competitor for other confronting uncertainties approaches, i.e. stochastic and Minimax Regret strategies. (author)
Uncertainty assessment for accelerator-driven systems
International Nuclear Information System (INIS)
Finck, P. J.; Gomes, I.; Micklich, B.; Palmiotti, G.
1999-01-01
The concept of a subcritical system driven by an external source of neutrons provided by an accelerator ADS (Accelerator Driver System) has been recently revived and is becoming more popular in the world technical community with active programs in Europe, Russia, Japan, and the U.S. A general consensus has been reached in adopting for the subcritical component a fast spectrum liquid metal cooled configuration. Both a lead-bismuth eutectic, sodium and gas are being considered as a coolant; each has advantages and disadvantages. The major expected advantage is that subcriticality avoids reactivity induced transients. The potentially large subcriticality margin also should allow for the introduction of very significant quantities of waste products (minor Actinides and Fission Products) which negatively impact the safety characteristics of standard cores. In the U.S. these arguments are the basis for the development of the Accelerator Transmutation of Waste (ATW), which has significant potential in reducing nuclear waste levels. Up to now, neutronic calculations have not attached uncertainties on the values of the main nuclear integral parameters that characterize the system. Many of these parameters (e.g., degree of subcriticality) are crucial to demonstrate the validity and feasibility of this concept. In this paper we will consider uncertainties related to nuclear data only. The present knowledge of the cross sections of many isotopes that are not usually utilized in existing reactors (like Bi, Pb-207, Pb-208, and also Minor Actinides and Fission Products) suggests that uncertainties in the integral parameters will be significantly larger than for conventional reactor systems, and this raises concerns on the neutronic performance of those systems
Uncertainty in air quality observations using low-cost sensors
Castell, Nuria; Dauge, Franck R.; Dongol, Rozina; Vogt, Matthias; Schneider, Philipp
2016-04-01
Air pollution poses a threat to human health, and the WHO has classified air pollution as the world's largest single environmental health risk. In Europe, the majority of the population lives in areas where air quality levels frequently exceed WHO's ambient air quality guidelines. The emergence of low-cost, user-friendly and very compact air pollution platforms allowing observations at high spatial resolution in near real-time, provides us with new opportunities to simultaneously enhance existing monitoring systems as well as enable citizens to engage in more active environmental monitoring (citizen science). However the data sets generated by low-cost sensors show often questionable data quality. For many sensors, neither their error characteristics nor how their measurement capability holds up over time or through a range of environmental conditions, have been evaluated. We have conducted an exhaustive evaluation of the commercial low-cost platform AQMesh (measuring NO, NO2, CO, O3, PM10 and PM2.5) in laboratory and in real-world conditions in the city of Oslo (Norway). Co-locations in field of 24 platforms were conducted over a 6 month period (April to September 2015) allowing to characterize the temporal variability in the performance. Additionally, the field performance included the characterization on different monitoring urban monitoring sites characteristic of both traffic and background conditions. All the evaluations have been conducted against CEN reference method analyzers maintained according to the Norwegian National Reference Laboratory quality system. The results show clearly that a good performance in laboratory does not imply similar performance in real-world outdoor conditions. Moreover, laboratory calibration is not suitable for subsequent measurements in urban environments. In order to reduce the errors, sensors require on-site field calibration. Even after such field calibration, the platforms show a significant variability in the performance
A probabilistic approach to cost and duration uncertainties in environmental decisions
International Nuclear Information System (INIS)
Boak, D.M.; Painton, L.
1996-01-01
Sandia National Laboratories has developed a method for analyzing life-cycle costs using probabilistic cost forecasting and utility theory to determine the most cost-effective alternatives for safe interim storage of radioactive materials. The method explicitly incorporates uncertainties in cost and storage duration by (1) treating uncertain component costs as random variables represented by probability distributions, (2) treating uncertain durations as chance nodes in a decision tree, and (3) using stochastic simulation tools to generate life-cycle cost forecasts for each storage alternative. The method applies utility functions to the forecasted costs to incorporate the decision maker's risk preferences, making it possible to compare alternatives on the basis of both cost and cost utility. Finally, the method is used to help identify key contributors to the uncertainty in forecasted costs to focus efforts aimed at reducing cost uncertainties. Where significant cost and duration uncertainties exist, and where programmatic decisions must be made despite these uncertainties, probabilistic forecasting techniques can yield important insights into decision alternatives, especially when used as part of a larger decision analysis framework and when properly balanced with deterministic analyses. Although the method is built around an interim storage example, it is potentially applicable to many other environmental decision problems
Cost Implications of Uncertainty in CO{sub 2} Storage Resource Estimates: A Review
Energy Technology Data Exchange (ETDEWEB)
Anderson, Steven T., E-mail: sanderson@usgs.gov [National Center, U.S. Geological Survey (United States)
2017-04-15
Carbon capture from stationary sources and geologic storage of carbon dioxide (CO{sub 2}) is an important option to include in strategies to mitigate greenhouse gas emissions. However, the potential costs of commercial-scale CO{sub 2} storage are not well constrained, stemming from the inherent uncertainty in storage resource estimates coupled with a lack of detailed estimates of the infrastructure needed to access those resources. Storage resource estimates are highly dependent on storage efficiency values or storage coefficients, which are calculated based on ranges of uncertain geological and physical reservoir parameters. If dynamic factors (such as variability in storage efficiencies, pressure interference, and acceptable injection rates over time), reservoir pressure limitations, boundaries on migration of CO{sub 2}, consideration of closed or semi-closed saline reservoir systems, and other possible constraints on the technically accessible CO{sub 2} storage resource (TASR) are accounted for, it is likely that only a fraction of the TASR could be available without incurring significant additional costs. Although storage resource estimates typically assume that any issues with pressure buildup due to CO{sub 2} injection will be mitigated by reservoir pressure management, estimates of the costs of CO{sub 2} storage generally do not include the costs of active pressure management. Production of saline waters (brines) could be essential to increasing the dynamic storage capacity of most reservoirs, but including the costs of this critical method of reservoir pressure management could increase current estimates of the costs of CO{sub 2} storage by two times, or more. Even without considering the implications for reservoir pressure management, geologic uncertainty can significantly impact CO{sub 2} storage capacities and costs, and contribute to uncertainty in carbon capture and storage (CCS) systems. Given the current state of available information and the
Analysis on Calibration and Uncertainty for TD-LTE Radio Test System
Directory of Open Access Journals (Sweden)
Zhang Weipeng
2014-06-01
Full Text Available TD-LTE base station radio test system measures radio signal with a required accuracy, so calibration need to be done for transmission path between base station and measurement instruments before test. Considering Transmitter OFF Power measurement within OFF period, modulated signal generator and spectrum analyzer inside test system is used for calibration, to get accurate transmission parameters of the paths, and to reduce test cost without more instruments. The paper describes the uncertainty of test system, analyzes uncertainty contribution of interface mismatch, calculates uncertainty for Transmitter OFF Power measurement, uncertainty is 1.193 dB, within the requirement of 3GPP specification.
Change and uncertainty in quantum systems
International Nuclear Information System (INIS)
Franson, J.D.
1996-01-01
A simple inequality shows that any change in the expectation value of an observable quantity must be associated with some degree of uncertainty. This inequality is often more restrictive than the Heisenberg uncertainty principle. copyright 1996 The American Physical Society
Intrinsic Uncertainties in Modeling Complex Systems.
Energy Technology Data Exchange (ETDEWEB)
Cooper, Curtis S; Bramson, Aaron L.; Ames, Arlo L.
2014-09-01
Models are built to understand and predict the behaviors of both natural and artificial systems. Because it is always necessary to abstract away aspects of any non-trivial system being modeled, we know models can potentially leave out important, even critical elements. This reality of the modeling enterprise forces us to consider the prospective impacts of those effects completely left out of a model - either intentionally or unconsidered. Insensitivity to new structure is an indication of diminishing returns. In this work, we represent a hypothetical unknown effect on a validated model as a finite perturba- tion whose amplitude is constrained within a control region. We find robustly that without further constraints, no meaningful bounds can be placed on the amplitude of a perturbation outside of the control region. Thus, forecasting into unsampled regions is a very risky proposition. We also present inherent difficulties with proper time discretization of models and representing in- herently discrete quantities. We point out potentially worrisome uncertainties, arising from math- ematical formulation alone, which modelers can inadvertently introduce into models of complex systems. Acknowledgements This work has been funded under early-career LDRD project #170979, entitled "Quantify- ing Confidence in Complex Systems Models Having Structural Uncertainties", which ran from 04/2013 to 09/2014. We wish to express our gratitude to the many researchers at Sandia who con- tributed ideas to this work, as well as feedback on the manuscript. In particular, we would like to mention George Barr, Alexander Outkin, Walt Beyeler, Eric Vugrin, and Laura Swiler for provid- ing invaluable advice and guidance through the course of the project. We would also like to thank Steven Kleban, Amanda Gonzales, Trevor Manzanares, and Sarah Burwell for their assistance in managing project tasks and resources.
Approaches for Managing Uncertainty in Learning Management Systems
Radwan, Nouran M.; Senousy, M. Badr; Riad, Alaa El Din M.
2016-01-01
The notion of uncertainty in expert systems is dealing with vague data, incomplete information, and imprecise knowledge. Different uncertainty types which are imprecision, vagueness, ambiguity, and inconsistence need different handling models. Uncertain knowledge representation and analysis is an essential issue.
Limitations of acceptability curves for presenting uncertainty in cost-effectiveness analysis
Groot Koerkamp, Bas; Hunink, M. G. Myriam; Stijnen, Theo; Hammitt, James K.; Kuntz, Karen M.; Weinstein, Milton C.
2007-01-01
Clinical journals increasingly illustrate uncertainty about the cost and effect of health care interventions using cost-effectiveness acceptability curves (CEACs). CEACs present the probability that each competing alternative is optimal for a range of values of the cost-effectiveness threshold. The
Optimum sizing of wind-battery systems incorporating resource uncertainty
International Nuclear Information System (INIS)
Roy, Anindita; Kedare, Shireesh B.; Bandyopadhyay, Santanu
2010-01-01
The inherent uncertainty of the wind is a major impediment for successful implementation of wind based power generation technology. A methodology has been proposed in this paper to incorporate wind speed uncertainty in sizing wind-battery system for isolated applications. The uncertainty associated with the wind speed is incorporated using chance constraint programming approach. For a pre-specified reliability requirement, a deterministic equivalent energy balance equation may be derived from the chance constraint that allows time series simulation of the entire system. This results in a generation of the entire set of feasible design options, satisfying different system level constraints, on a battery capacity vs. generator rating diagram, also known as the design space. The proposed methodology highlights the trade-offs between the wind turbine rating, rotor diameter and the battery size for a given reliability of power supply. The optimum configuration is chosen on the basis of the minimum cost of energy (US$/kWh). It is shown with the help of illustrative examples that the proposed methodology is generic and flexible to incorporate alternate sub-component models. (author)
Estimating the costs of nuclear power: benchmarks and uncertainties
International Nuclear Information System (INIS)
Leveque, Francois
2013-05-01
The debate on this topic is fairly confusing. Some present electricity production using nuclear power as an affordable solution, others maintain it is too expensive. These widely divergent views prompt fears among consumers and voters that they are being manipulated: each side is just defending its own interests and the true cost of nuclear power is being concealed. Companies and non-government organizations certainly adopt whatever position suits them best. But at the same time, the notion of just one 'true' cost is misleading. As we shall see in this paper there is no such thing as the cost of nuclear power: we must reason in terms of costs and draw a distinction between a private cost and a social cost. The private cost is what an operator examines before deciding whether it is opportune to build a new nuclear power station. This cost varies between different investors, particularly as a function of their attitude to risks. On the other hand the social cost weighs on society, which may take into account the risk of proliferation, or the benefits of avoiding carbon-dioxide emissions, among others. The cost of actually building new plant differs from one country to the next. So deciding whether nuclear power is profitable or not, a benefit for society or not, does not involve determining the real cost, but rather compiling data, developing methods and formulating hypotheses. It is not as easy as inundating the general public with contradictory figures, but it is a more effective way of casting light on economic decisions by industry and government. Without evaluating the costs it is impossible to establish the cost price, required to compare electricity production using nuclear power and rival technologies. Would it be preferable to build a gas-powered plant, a nuclear reactor or a wind farm? Which technology yields the lowest cost per KWh? Under what conditions - financial terms, regulatory framework, carbon pricing - will private investors see an adequate return
Forecasting the Number of Soil Samples Required to Reduce Remediation Cost Uncertainty
Demougeot-Renard, Hélène; de Fouquet, Chantal; Renard, Philippe
2008-01-01
Sampling scheme design is an important step in the management of polluted sites. It largely controls the accuracy of remediation cost estimates. In practice, however, sampling is seldom designed to comply with a given level of remediation cost uncertainty. In this paper, we present a new technique that allows one to estimate of the number of samples that should be taken at a given stage of investigation to reach a forecasted level of accuracy. The uncertainty is expressed both in terms of vol...
International Nuclear Information System (INIS)
Farrell, Niall; Donoghue, Cathal O’; Morrissey, Karyn
2015-01-01
Wave Energy Conversion (WEC) devices are at a pre-commercial stage of development with feasibility studies sensitive to uncertainties surrounding assumed input costs. This may affect decision making. This paper analyses the impact these uncertainties may have on investor, developer and policymaker decisions using an Irish case study. Calibrated to data present in the literature, a probabilistic methodology is shown to be an effective means to carry this out. Value at Risk (VaR) and Conditional Value at Risk (CVaR) metrics are used to quantify the certainty of achieving a given cost or return on investment. We analyse the certainty of financial return provided by the proposed Irish Feed-in Tariff (FiT) policy. The influence of cost reduction through bulk discount is also discussed, with cost reduction targets for developers identified. Uncertainty is found to have a greater impact on the profitability of smaller installations and those subject to lower rates of cost reduction. This paper emphasises that a premium is required to account for cost uncertainty when setting FiT rates. By quantifying uncertainty, a means to specify an efficient premium is presented. - Highlights: • Probabilistic model quantifies uncertainty for wave energy feasibility analyses. • Methodology presented and applied to an Irish case study. • A feed-in tariff premium of 3–4 c/kWh required to account for cost uncertainty. • Sensitivity of uncertainty and cost to rates of technological change analysed. • Use of probabilistic model for investors and developers also demonstrated
Uncertainty and sensitivity analyses of ballast life-cycle cost and payback period
Mcmahon, James E.
2000-01-01
The paper introduces an innovative methology for evaluating the relative significance of energy-efficient technologies applied to fluorescent lamp ballasts. The method involves replacing the point estimates of life cycle cost of the ballasts with uncertainty distributions reflecting the whole spectrum of possible costs, and the assessed probability associated with each value. The results of uncertainty and sensitivity analyses will help analysts reduce effort in data collection and carry on a...
Using performance indicators to reduce cost uncertainty of China's CO2 mitigation goals
International Nuclear Information System (INIS)
Xu, Yuan
2013-01-01
Goals on absolute emissions and intensity play key roles in CO 2 mitigation. However, like cap-and-trade policies with price uncertainty, they suffer from significant uncertainty in abatement costs. This article examines whether an indicator could be established to complement CO 2 mitigation goals and help reduce cost uncertainty with a particular focus on China. Performance indicators on CO 2 emissions per unit of energy consumption could satisfy three criteria: compared with the mitigation goals, (i) they are more closely associated with active mitigation efforts and (ii) their baselines have more stable projections from historical trajectories. (iii) Their abatement costs are generally higher than other mitigation methods, particularly energy efficiency and conservation. Performance indicators could be used in the following way: if a CO 2 goal on absolute emissions or intensity is attained, the performance indicator should still reach a lower threshold as a cost floor. If the goal cannot be attained, an upper performance threshold should be achieved as a cost ceiling. The narrower cost uncertainty may encourage wider and greater mitigation efforts. - Highlights: ► CO 2 emissions per unit of energy consumption could act as performance indicators. ► Performance indicators are more closely related to active mitigation activities. ► Performance indicators have more stable historical trajectories. ► Abatement costs are higher for performance indicators than for other activities. ► Performance thresholds could reduce the cost uncertainty of CO 2 mitigation goals.
Model Uncertainty for Bilinear Hysteretic Systems
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Thoft-Christensen, Palle
1984-01-01
. The statistical uncertainty -due to lack of information can e.g. be taken into account by describing the variables by predictive density functions, Veneziano [2). In general, model uncertainty is the uncertainty connected with mathematical modelling of the physical reality. When structural reliability analysis...... is related to the concept of a failure surface (or limit state surface) in the n-dimensional basic variable space then model uncertainty is at least due to the neglected variables, the modelling of the failure surface and the computational technique used. A more precise definition is given in section 2...
International Nuclear Information System (INIS)
DeMuth, S.
1998-01-01
Enhanced Sludge Washing (ESW) has been selected to reduce the amount of sludge-based underground storage tank (UST) high-level waste at the Hanford site. During the past several years, studies have been conducted to determine the cost savings derived from the implementation of ESW. The tank waste inventory and ESW performance continues to be revised as characterization and development efforts advance. This study provides a new cost savings estimate based upon the most recent inventory and ESW performance revisions, and includes an estimate of the associated cost uncertainty. Whereas the author's previous cost savings estimates for ESW were compared against no sludge washing, this study assumes the baseline to be simple water washing which more accurately reflects the retrieval activity along. The revised ESW cost savings estimate for all UST waste at Hanford is $6.1 B ± $1.3 B within 95% confidence. This is based upon capital and operating cost savings, but does not include development costs. The development costs are assumed negligible since they should be at least an order of magnitude less than the savings. The overall cost savings uncertainty was derived from process performance uncertainties and baseline remediation cost uncertainties, as determined by the author's engineering judgment
Life cycle cost analysis of wind power considering stochastic uncertainties
International Nuclear Information System (INIS)
Li, Chiao-Ting; Peng, Huei; Sun, Jing
2014-01-01
This paper presents a long-term cost analysis of wind power and compares its competitiveness to non-renewable generating technologies. The analysis considers several important attributes related to wind intermittency that are sometimes ignored in traditional generation planning or LCOE (levelized cost of energy) studies, including the need for more nameplate capacity due to intermittency, hourly fluctuations in wind outputs and cost for reserves. The competitiveness of wind power is assessed by evaluating four scenarios: 1) adding natural gas generating capacity to the power grid; 2) adding coal generating capacity to the power grid; 3) adding wind capacity to the power grid; and, 4) adding wind capacity and energy storage to the power grid where an energy storage device is used to cover wind intermittency. A case study in the state of Michigan is presented to demonstrate the use of the proposed methodology, in which a time horizon from 2010 to 2040 is considered. The results show that wind energy will still be more expensive than natural gas power plants in the next three decades, but will be cheaper than coal capacities if wind intermittency is mitigated. Furthermore, if the costs of carbon emissions and environmental externalities are considered, wind generation will be a competitive option for grid capacity expansion. - Highlights: • The competitiveness of wind power is analyzed via life cycle cost analysis. • Wind intermittency and reserve costs are explicitly considered in the analysis. • Results show that wind is still more expensive than natural gas power plants. • Wind can be cheaper than coal capacities if wind intermittency is mitigated. • Wind will be competitive if costs of carbon emissions are considered
Dynamic Uncertainty for Compensated Second-Order Systems
Directory of Open Access Journals (Sweden)
Clemens Elster
2010-08-01
Full Text Available The compensation of LTI systems and the evaluation of the according uncertainty is of growing interest in metrology. Uncertainty evaluation in metrology ought to follow specific guidelines, and recently two corresponding uncertainty evaluation schemes have been proposed for FIR and IIR filtering. We employ these schemes to compare an FIR and an IIR approach for compensating a second-order LTI system which has relevance in metrology. Our results suggest that the FIR approach is superior in the sense that it yields significantly smaller uncertainties when real-time evaluation of uncertainties is desired.
Comparing Cost Of New Supply Chain Designs Under Uncertainty
DEFF Research Database (Denmark)
Wæhrens, Brian Vejrum; Kristensen, Jesper; Asmussen, Jesper Normann
2016-01-01
Accounting, Operational Modelling and SCM inform decision making for new SCDs. Through four embedded cases, a gap is found between the practice of a global OEM and literature. Results shows complications when assessing SCDs due to limited understanding of the internal activity costs, supply chain dynamics...
Optimal Time to Invest Energy Storage System under Uncertainty Conditions
Directory of Open Access Journals (Sweden)
Yongma Moon
2014-04-01
Full Text Available This paper proposes a model to determine the optimal investment time for energy storage systems (ESSs in a price arbitrage trade application under conditions of uncertainty over future profits. The adoption of ESSs can generate profits from price arbitrage trade, which are uncertain because the future marginal prices of electricity will change depending on supply and demand. In addition, since the investment is optional, an investor can delay adopting an ESS until it becomes profitable, and can decide the optimal time. Thus, when we evaluate this investment, we need to incorporate the investor’s option which is not captured by traditional evaluation methods. In order to incorporate these aspects, we applied real option theory to our proposed model, which provides an optimal investment threshold. Our results concerning the optimal time to invest show that if future profits that are expected to be obtained from arbitrage trade become more uncertain, an investor needs to wait longer to invest. Also, improvement in efficiency of ESSs can reduce the uncertainty of arbitrage profit and, consequently, the reduced uncertainty enables earlier ESS investment, even for the same power capacity. Besides, when a higher rate of profits is expected and ESS costs are higher, an investor needs to wait longer. Also, by comparing a widely used net present value model to our real option model, we show that the net present value method underestimates the value for ESS investment and misleads the investor to make an investment earlier.
Fuzzy ABC: modeling the uncertainty in environmental cost allocation
Borba, José Alonso; Murcia, Fernando Dal Ri; Maior, Cesar Duarte Souto
2007-01-01
In many cases, preventing pollution and environmental destruction is cheaper than remedying these damages. In this sense, environmental cost allocation enables a better visualization and analysis of a product's profitability. However, the environmental allocation process involves estimated information and assumes linearity between activity consumption and product that is not real in many cases. In order to handle this not-linearity, this research presents a methodology based on fuzzy logic co...
Uncertainty and sensitivity analyses of ballast life-cycle cost and payback period
Energy Technology Data Exchange (ETDEWEB)
McMahon, James E.; Liu, Xiaomin; Turiel, Ike; Hakim, Sajid; Fisher, Diane
2000-06-01
The paper introduces an innovative methodology for evaluating the relative significance of energy-efficient technologies applied to fluorescent lamp ballasts. The method involves replacing the point estimates of life cycle cost of the ballasts with uncertainty distributions reflecting the whole spectrum of possible costs, and the assessed probability associated with each value. The results of uncertainty and sensitivity analyses will help analysts reduce effort in data collection and carry on analysis more efficiently. These methods also enable policy makers to gain an insightful understanding of which efficient technology alternatives benefit or cost what fraction of consumers, given the explicit assumptions of the analysis.
Quantifying uncertainty in LCA-modelling of waste management systems
DEFF Research Database (Denmark)
Clavreul, Julie; Guyonnet, D.; Christensen, Thomas Højlund
2012-01-01
Uncertainty analysis in LCA studies has been subject to major progress over the last years. In the context of waste management, various methods have been implemented but a systematic method for uncertainty analysis of waste-LCA studies is lacking. The objective of this paper is (1) to present...... the sources of uncertainty specifically inherent to waste-LCA studies, (2) to select and apply several methods for uncertainty analysis and (3) to develop a general framework for quantitative uncertainty assessment of LCA of waste management systems. The suggested method is a sequence of four steps combining...
Research of Uncertainty Reasoning in Pineapple Disease Identification System
Liu, Liqun; Fan, Haifeng
In order to deal with the uncertainty of evidences mostly existing in pineapple disease identification system, a reasoning model based on evidence credibility factor was established. The uncertainty reasoning method is discussed,including: uncertain representation of knowledge, uncertain representation of rules, uncertain representation of multi-evidences and update of reasoning rules. The reasoning can fully reflect the uncertainty in disease identification and reduce the influence of subjective factors on the accuracy of the system.
Summary of cost projection for regulatory uncertainties in the back end of the fuel cycle
International Nuclear Information System (INIS)
Raudenbush, M.H.; Geller, L.
1977-01-01
Fuel recycle cost deviations resulting from regulatory changes in the back end of the fuel cycle are examined from a number of different data sources, and three potentially large cost uncertainties are identified; HLW disposal, alpha-waste criteria, and in-plant material control/accountability for safeguards. Present and past methods of regulatory cost effectiveness determinations are critiqued and in some cases found wanting
Indian Academy of Sciences (India)
To reflect this uncertainty in the climate scenarios, the use of AOGCMs that explicitly simulate the carbon cycle and chemistry of all the substances are needed. The Hadley Centre has developed a version of the climate model that allows the effect of climate change on the carbon cycle and its feedback into climate, to be ...
International Nuclear Information System (INIS)
Silva, T.A. da
1988-01-01
The comparison between the uncertainty method recommended by International Atomic Energy Agency (IAEA) and the and the International Weight and Measure Commitee (CIPM) are showed, for the calibration of clinical dosimeters in the secondary standard Dosimetry Laboratory (SSDL). (C.G.C.) [pt
Using interpolation to estimate system uncertainty in gene expression experiments.
Directory of Open Access Journals (Sweden)
Lee J Falin
Full Text Available The widespread use of high-throughput experimental assays designed to measure the entire complement of a cell's genes or gene products has led to vast stores of data that are extremely plentiful in terms of the number of items they can measure in a single sample, yet often sparse in the number of samples per experiment due to their high cost. This often leads to datasets where the number of treatment levels or time points sampled is limited, or where there are very small numbers of technical and/or biological replicates. Here we introduce a novel algorithm to quantify the uncertainty in the unmeasured intervals between biological measurements taken across a set of quantitative treatments. The algorithm provides a probabilistic distribution of possible gene expression values within unmeasured intervals, based on a plausible biological constraint. We show how quantification of this uncertainty can be used to guide researchers in further data collection by identifying which samples would likely add the most information to the system under study. Although the context for developing the algorithm was gene expression measurements taken over a time series, the approach can be readily applied to any set of quantitative systems biology measurements taken following quantitative (i.e. non-categorical treatments. In principle, the method could also be applied to combinations of treatments, in which case it could greatly simplify the task of exploring the large combinatorial space of future possible measurements.
Different approaches to overcome uncertainties of production systems
Azizi, Amir; Sorooshian, Shahryar
2015-05-01
This study presented a comprehensive review on the understanding of uncertainty and the current approaches that have been proposed to handle the uncertainties in the production systems. This paper classified proposed approaches into 11 groups. The paper studied 114 scholarly papers through various international journals. The paper added the latest findings to the body of knowledge to the current reservoir of understanding of the production uncertainties. Thus, the paper prepared the needs of researchers and practitioners for easy references in this area. This review also provided an excellent source to continue further studies on how to deal with the uncertainties of production system.
International Nuclear Information System (INIS)
Violette, D.; Lang, C.
1990-01-01
Utility demand and supply-side planners will face new challenges from environmental regulations. Under current proposals, every ton of pollutant will have a cost to utilities, not just the tons that put them over the allowable limit. Planners will have to account for these new costs. To do this, planners need to start tracking emissions implementation actions today, and begin strategies for future regulatory changes. Current legislative proposals include a tax on the carbon content of fuels to curb emissions of greenhouse gases and substantial reductions in sulfur dioxide and nitrogen oxide emissions. The important issue for planners is the flexible compliance requirements within these regulatory changes. The acid rain proposals, for example, include a market-based emissions trading system for emissions allowances. Whenever there is a competitive market, there are market risks, and potential winners and losers. Utilities need to be prepared to analyze and mitigate these risks. Integrated least cost planing is one way a utility will have to meet this challenge. Planning involves uncertainty and risk. The wide array of compliance choices create countless combinations of strategies for utilities to comply with the new emissions regulations. This paper discusses new compliance strategies, demand-side management (DSM) as a compliance strategy, solutions to DSM traps, and the compliance strategy game
International Nuclear Information System (INIS)
Yin, Hao; Pizzol, Massimo; Xu, Linyu
2017-01-01
Some cities in China are facing serious air pollution problems including high concentrations of particles, SO 2 and NO x . Exposure to PM2.5, one of the primary air pollutants in many cities in China, is highly correlated with various adverse health impacts and ultimately represents a cost for society. The aim of this study is to assess health impacts and external costs related to PM2.5 pollution in Beijing, China with different baseline concentrations and valuation methods. The idea is to provide a reasonable estimate of the total health impacts and external cost due to PM2.5 pollution, as well as a quantification of the relevant uncertainty. PM2.5 concentrations were retrieved for the entire 2012 period in 16 districts of Beijing. The various PM2.5 related health impacts were identified and classified to avoid double counting. Exposure-response coefficients were then obtained from literature. Both the value of statistical life (VSL) and the amended human capital (AHC) approach were applied for external costs estimation, which could provide the upper and lower bound of the external costs due to PM2.5. To fully understand the uncertainty levels, the external cost distribution was determined via Monte Carlo simulation based on the uncertainty of the parameters such as PM2.5 concentration, exposure-response coefficients, and economic cost per case. The results showed that the external costs were equivalent to around 0.3% (AHC, China's guideline: C 0 = 35 μg/m 3 ) to 0.9% (VSL, WHO guideline: C 0 = 10 μg/m 3 ) of regional GDP depending on the valuation method and on the assumed baseline PM2.5 concentration (C 0 ). Among all the health impacts, the economic loss due to premature deaths accounted for more than 80% of the overall external costs. The results of this study could help policymakers prioritizing the PM2.5 pollution control interventions and internalize the external costs through the application of economic policy instruments. - Highlights:
Advice under uncertainty in the marine system
DEFF Research Database (Denmark)
Dankel, Dorothy J.; Aps, Robert; Padda, Gurpreet
2012-01-01
lacking. Fisheries science that gives advice to policy-making is plagued by uncertainties; the stakes of the policies are high and value-laden and need therefore to be treated as an example of “post-normal science” (PNS). To achieve robust governance, understanding of the characteristics and implications...
Quality cost system in electronics
International Nuclear Information System (INIS)
Denzer, H.O.
1978-01-01
A description is presented of a formal cost of quality system used in an electronic manufacturing facility. The system elements and reports are illustrated. Examples of the use of a quality cost system to measure quality performance and to improve product quality are included. A comparison to industry averages for quality costs is made. The paper attempts to show that the collection and use of quality costs are an aid to management and can be accompanied by improved product quality
How to deal with climate change uncertainty in the planning of engineering systems
Spackova, Olga; Dittes, Beatrice; Straub, Daniel
2016-04-01
The effect of extreme events such as floods on the infrastructure and built environment is associated with significant uncertainties: These include the uncertain effect of climate change, uncertainty on extreme event frequency estimation due to limited historic data and imperfect models, and, not least, uncertainty on future socio-economic developments, which determine the damage potential. One option for dealing with these uncertainties is the use of adaptable (flexible) infrastructure that can easily be adjusted in the future without excessive costs. The challenge is in quantifying the value of adaptability and in finding the optimal sequence of decision. Is it worth to build a (potentially more expensive) adaptable system that can be adjusted in the future depending on the future conditions? Or is it more cost-effective to make a conservative design without counting with the possible future changes to the system? What is the optimal timing of the decision to build/adjust the system? We develop a quantitative decision-support framework for evaluation of alternative infrastructure designs under uncertainties, which: • probabilistically models the uncertain future (trough a Bayesian approach) • includes the adaptability of the systems (the costs of future changes) • takes into account the fact that future decisions will be made under uncertainty as well (using pre-posterior decision analysis) • allows to identify the optimal capacity and optimal timing to build/adjust the infrastructure. Application of the decision framework will be demonstrated on an example of flood mitigation planning in Bavaria.
International Nuclear Information System (INIS)
Spadaro, Joseph V.; Rabl, Ari
2008-01-01
Whereas the uncertainty of environmental impacts and damage costs is usually estimated by means of a Monte Carlo calculation, this paper shows that most (and in many cases all) of the uncertainty calculation involves products and/or sums of products and can be accomplished with an analytic solution which is simple and transparent. We present our own assessment of the component uncertainties and calculate the total uncertainty for the impacts and damage costs of the classical air pollutants; results for a Monte Carlo calculation for the dispersion part are also shown. The distribution of the damage costs is approximately lognormal and can be characterized in terms of geometric mean μ g and geometric standard deviation σ g , implying that the confidence interval is multiplicative. We find that for the classical air pollutants σ g is approximately 3 and the 68% confidence interval is [μ g / σ g , μ g σ g ]. Because the lognormal distribution is highly skewed for large σ g , the median is significantly smaller than the mean. We also consider the case where several lognormally distributed damage costs are added, for example to obtain the total damage cost due to all the air pollutants emitted by a power plant, and we find that the relative error of the sum can be significantly smaller than the relative errors of the summands. Even though the distribution for such sums is not exactly lognormal, we present a simple lognormal approximation that is quite adequate for most applications
Using cost-benefit concepts in design floods improves communication of uncertainty
Ganora, Daniele; Botto, Anna; Laio, Francesco; Claps, Pierluigi
2017-04-01
Flood frequency analysis, i.e. the study of the relationships between the magnitude and the rarity of high flows in a river, is the usual procedure adopted to assess flood hazard, preliminary to the plan/design of flood protection measures. It grounds on the fit of a probability distribution to the peak discharge values recorded in gauging stations and the final estimates over a region are thus affected by uncertainty, due to the limited sample availability and of the possible alternatives in terms of the probabilistic model and the parameter estimation methods used. In the last decade, the scientific community dealt with this issue by developing a number of methods to quantify such uncertainty components. Usually, uncertainty is visually represented through confidence bands, which are easy to understand, but are not yet demonstrated to be useful for design purposes: they usually disorient decision makers, as the design flood is no longer univocally defined, making the decision process undetermined. These considerations motivated the development of the uncertainty-compliant design flood estimator (UNCODE) procedure (Botto et al., 2014) that allows one to select meaningful flood design values accounting for the associated uncertainty by considering additional constraints based on cost-benefit criteria. This method suggests an explicit multiplication factor that corrects the traditional (without uncertainty) design flood estimates to incorporate the effects of uncertainty in the estimate at the same safety level. Even though the UNCODE method was developed for design purposes, it can represent a powerful and robust tool to help clarifying the effects of the uncertainty in statistical estimation. As the process produces increased design flood estimates, this outcome demonstrates how uncertainty leads to more expensive flood protection measures, or insufficiency of current defenses. Moreover, the UNCODE approach can be used to assess the "value" of data, as the costs
Sensitivity of nuclear fuel cycle cost to uncertainties in nuclear data
International Nuclear Information System (INIS)
Harris, D.R.; Becker, M.; Parvez, A.; Ryskamp, J.M.
1979-01-01
A sensitivity analysis system is developed for assessing the economic implications of uncertainties in nuclear data and related computational methods for light water power reactors. Results of the sensitivity analysis indicate directions for worthwhile improvements in data and methods. Benefits from improvements in data and methods are related to reduction of margins provided by designers to ensure meeting reactor and fuel objectives. Sensitivity analyses are carried out using the batch depletion code FASTCELL, the core analysis code FASTCORE, and the reactor cost code COSTR. FASTCELL depletes a cell using methods comparable to industry cell codes except for a few-group treatment of cell flux distribution. FASTCORE is used with the Haling strategy of fixed power sharing among batches in the core. COSTR computes costs using components and techniques as in industry costing codes, except that COSTR uses fixed payment schedules. Sensitivity analyses are carried out for large commercial boiling and pressurized water reactors. Each few-group nuclear parameter is changed, and initial enrichment is also changed so as to keep the end-of-cycle core multiplication factor unchanged, i.e., to preserve cycle time at the demand power. Sensitivities of equilibrium fuel cycle cost are determined with respect to approx. 300 few-group nuclear parameters, both for a normal fuel cycle and for a throwaway fuel cycle. Particularly large dollar implications are found for thermal and resonance range cross sections in fissile and fertile materials. Sensitivities constrained by adjustment of fission neutron yield so as to preserve agreement with zero exposure integral data also are computed
Communicating uncertainty in cost-benefit analysis : A cognitive psychological perspective
Mouter, N.; Holleman, M.; Calvert, S.C.; Annema, J.A.
2013-01-01
Based on a cognitive psychological theory, this paper aims to improve the communication of uncertainty in Cost-Benefit Analysis. The theory is based on different cognitive-personality and cognitive-social psychological constructs that may help explain individual differences in the processing of
Pan, Yilin
2016-01-01
Given the necessity to bridge the gap between what happened and what is likely to happen, this paper aims to explore how to apply Bayesian inference to cost-effectiveness analysis so as to capture the uncertainty of a ratio-type efficiency measure. The first part of the paper summarizes the characteristics of the evaluation data that are commonly…
Peter, Winter
2005-01-01
This paper aims at providing an insight into Japanese cost accounting. Firstly, the development of cost accounting in Japan is delineated. Subsequently, the cost accounting systems codified in the Japanese cost accounting standard are analysed based on the classification according to Hoitsch/Schmitz. Lastly, a critical appraisal of the cost accounting systems of the Japanese cost accounting standard as well as a comparison to German and American cost accounting systems are conducted.
Uncertainty of Water-hammer Loads for Safety Related Systems
Energy Technology Data Exchange (ETDEWEB)
Lee, Seung Chan; Yoon, Duk Joo [Korea Hydro and Nuclear Power Co., LT., Daejeon (Korea, Republic of)
2013-10-15
In this study, the basic methodology is base on ISO GUM (Guide to the Expression of Uncertainty in Measurements). For a given gas void volumes in the discharge piping, the maximum pressure of water hammer is defined in equation. From equation, uncertainty parameter is selected as U{sub s} (superficial velocity for the specific pipe size and corresponding area) of equation. The main uncertainty parameter (U{sub s}) is estimated by measurement method and Monte Carlo simulation. Two methods are in good agreement with the extended uncertainty. Extended uncertainty of the measurement and Monte Carlo simulation is 1.30 and 1.34 respectively in 95% confidence interval. In 99% confidence interval, the uncertainties are 1.95 and 1.97 respectively. NRC Generic Letter 2008-01 requires nuclear power plant operators to evaluate the possibility of noncondensable gas accumulation for the Emergency Core Cooling System. Specially, gas accumulation can result in system pressure transient in pump discharge piping at a pump start. Consequently, this evolves into a gas water, a water-hammer event and the force imbalances on the piping segments. In this paper, MCS (Monte Carlo Simulation) method is introduced in estimating the uncertainty of water hammer. The aim is to evaluate the uncertainty of the water hammer estimation results carried out by KHNP CRI in 2013.
Task uncertainty can account for mixing and switch costs in task-switching.
Directory of Open Access Journals (Sweden)
Patrick S Cooper
Full Text Available Cognitive control is required in situations that involve uncertainty or change, such as when resolving conflict, selecting responses and switching tasks. Recently, it has been suggested that cognitive control can be conceptualised as a mechanism which prioritises goal-relevant information to deal with uncertainty. This hypothesis has been supported using a paradigm that requires conflict resolution. In this study, we examine whether cognitive control during task switching is also consistent with this notion. We used information theory to quantify the level of uncertainty in different trial types during a cued task-switching paradigm. We test the hypothesis that differences in uncertainty between task repeat and task switch trials can account for typical behavioural effects in task-switching. Increasing uncertainty was associated with less efficient performance (i.e., slower and less accurate, particularly on switch trials and trials that afford little opportunity for advance preparation. Interestingly, both mixing and switch costs were associated with a common episodic control process. These results support the notion that cognitive control may be conceptualised as an information processor that serves to resolve uncertainty in the environment.
Task Uncertainty Can Account for Mixing and Switch Costs in Task-Switching
Rennie, Jaime L.
2015-01-01
Cognitive control is required in situations that involve uncertainty or change, such as when resolving conflict, selecting responses and switching tasks. Recently, it has been suggested that cognitive control can be conceptualised as a mechanism which prioritises goal-relevant information to deal with uncertainty. This hypothesis has been supported using a paradigm that requires conflict resolution. In this study, we examine whether cognitive control during task switching is also consistent with this notion. We used information theory to quantify the level of uncertainty in different trial types during a cued task-switching paradigm. We test the hypothesis that differences in uncertainty between task repeat and task switch trials can account for typical behavioural effects in task-switching. Increasing uncertainty was associated with less efficient performance (i.e., slower and less accurate), particularly on switch trials and trials that afford little opportunity for advance preparation. Interestingly, both mixing and switch costs were associated with a common episodic control process. These results support the notion that cognitive control may be conceptualised as an information processor that serves to resolve uncertainty in the environment. PMID:26107646
Robust Performance of Systems with Structured Uncertainties in State Space
Zhou, K.; Khargonekar, P.P.; Stoustrup, Jakob; Niemann, H.H.
1995-01-01
This paper considers robust performance analysis and state feedback design for systems with time-varying parameter uncertainties. The notion of a strongly robust % performance criterion is introduced, and its applications in robust performance analysis and synthesis for nominally linear systems with time-varying uncertainties are discussed and compared with the constant scaled small gain criterion. It is shown that most robust performance analysis and synthesisproblems under this strongly rob...
Site utility system optimization with operation adjustment under uncertainty
International Nuclear Information System (INIS)
Sun, Li; Gai, Limei; Smith, Robin
2017-01-01
Highlights: • Uncertainties are classified into time-based and probability-based uncertain factors. • Multi-period operation and recourses deal with uncertainty implementation. • Operation scheduling are specified at the design stage to deal with uncertainties. • Steam mains superheating affects steam distribution and power generation in the system. - Abstract: Utility systems must satisfy process energy and power demands under varying conditions. The system performance is decided by the system configuration and individual equipment operating load for boilers, gas turbines, steam turbines, condensers, and let down valves. Steam mains conditions in terms of steam pressures and steam superheating also play important roles on steam distribution in the system and power generation by steam expansion in steam turbines, and should be included in the system optimization. Uncertainties such as process steam power demand changes and electricity price fluctuations should be included in the system optimization to eliminate as much as possible the production loss caused by steam power deficits due to uncertainties. In this paper, uncertain factors are classified into time-based and probability-based uncertain factors, and operation scheduling containing multi-period equipment load sharing, redundant equipment start up, and electricity import to compensate for power deficits, have been presented to deal with the happens of uncertainties, and are formulated as a multi-period item and a recourse item in the optimization model. There are two case studies in this paper. One case illustrates the system design to determine system configuration, equipment selection, and system operation scheduling at the design stage to deal with uncertainties. The other case provides operational optimization scenarios for an existing system, especially when the steam superheating varies. The proposed method can provide practical guidance to system energy efficiency improvement.
Yin, Hao; Pizzol, Massimo; Xu, Linyu
2017-07-01
Some cities in China are facing serious air pollution problems including high concentrations of particles, SO 2 and NO x . Exposure to PM2.5, one of the primary air pollutants in many cities in China, is highly correlated with various adverse health impacts and ultimately represents a cost for society. The aim of this study is to assess health impacts and external costs related to PM2.5 pollution in Beijing, China with different baseline concentrations and valuation methods. The idea is to provide a reasonable estimate of the total health impacts and external cost due to PM2.5 pollution, as well as a quantification of the relevant uncertainty. PM2.5 concentrations were retrieved for the entire 2012 period in 16 districts of Beijing. The various PM2.5 related health impacts were identified and classified to avoid double counting. Exposure-response coefficients were then obtained from literature. Both the value of statistical life (VSL) and the amended human capital (AHC) approach were applied for external costs estimation, which could provide the upper and lower bound of the external costs due to PM2.5. To fully understand the uncertainty levels, the external cost distribution was determined via Monte Carlo simulation based on the uncertainty of the parameters such as PM2.5 concentration, exposure-response coefficients, and economic cost per case. The results showed that the external costs were equivalent to around 0.3% (AHC, China's guideline: C 0 = 35 μg/m 3 ) to 0.9% (VSL, WHO guideline: C 0 = 10 μg/m 3 ) of regional GDP depending on the valuation method and on the assumed baseline PM2.5 concentration (C 0 ). Among all the health impacts, the economic loss due to premature deaths accounted for more than 80% of the overall external costs. The results of this study could help policymakers prioritizing the PM2.5 pollution control interventions and internalize the external costs through the application of economic policy instruments. Copyright © 2017
McCaffrey, Nikki; Agar, Meera; Harlum, Janeane; Karnon, Jonathon; Currow, David; Eckermann, Simon
2015-01-01
Comparing multiple, diverse outcomes with cost-effectiveness analysis (CEA) is important, yet challenging in areas like palliative care where domains are unamenable to integration with survival. Generic multi-attribute utility values exclude important domains and non-health outcomes, while partial analyses-where outcomes are considered separately, with their joint relationship under uncertainty ignored-lead to incorrect inference regarding preferred strategies. The objective of this paper is to consider whether such decision making can be better informed with alternative presentation and summary measures, extending methods previously shown to have advantages in multiple strategy comparison. Multiple outcomes CEA of a home-based palliative care model (PEACH) relative to usual care is undertaken in cost disutility (CDU) space and compared with analysis on the cost-effectiveness plane. Summary measures developed for comparing strategies across potential threshold values for multiple outcomes include: expected net loss (ENL) planes quantifying differences in expected net benefit; the ENL contour identifying preferred strategies minimising ENL and their expected value of perfect information; and cost-effectiveness acceptability planes showing probability of strategies minimising ENL. Conventional analysis suggests PEACH is cost-effective when the threshold value per additional day at home (1) exceeds $1,068 or dominated by usual care when only the proportion of home deaths is considered. In contrast, neither alternative dominate in CDU space where cost and outcomes are jointly considered, with the optimal strategy depending on threshold values. For example, PEACH minimises ENL when 1=$2,000 and 2=$2,000 (threshold value for dying at home), with a 51.6% chance of PEACH being cost-effective. Comparison in CDU space and associated summary measures have distinct advantages to multiple domain comparisons, aiding transparent and robust joint comparison of costs and multiple
McCaffrey, Nikki; Agar, Meera; Harlum, Janeane; Karnon, Jonathon; Currow, David; Eckermann, Simon
2015-01-01
Introduction Comparing multiple, diverse outcomes with cost-effectiveness analysis (CEA) is important, yet challenging in areas like palliative care where domains are unamenable to integration with survival. Generic multi-attribute utility values exclude important domains and non-health outcomes, while partial analyses—where outcomes are considered separately, with their joint relationship under uncertainty ignored—lead to incorrect inference regarding preferred strategies. Objective The objective of this paper is to consider whether such decision making can be better informed with alternative presentation and summary measures, extending methods previously shown to have advantages in multiple strategy comparison. Methods Multiple outcomes CEA of a home-based palliative care model (PEACH) relative to usual care is undertaken in cost disutility (CDU) space and compared with analysis on the cost-effectiveness plane. Summary measures developed for comparing strategies across potential threshold values for multiple outcomes include: expected net loss (ENL) planes quantifying differences in expected net benefit; the ENL contour identifying preferred strategies minimising ENL and their expected value of perfect information; and cost-effectiveness acceptability planes showing probability of strategies minimising ENL. Results Conventional analysis suggests PEACH is cost-effective when the threshold value per additional day at home ( 1) exceeds $1,068 or dominated by usual care when only the proportion of home deaths is considered. In contrast, neither alternative dominate in CDU space where cost and outcomes are jointly considered, with the optimal strategy depending on threshold values. For example, PEACH minimises ENL when 1=$2,000 and 2=$2,000 (threshold value for dying at home), with a 51.6% chance of PEACH being cost-effective. Conclusion Comparison in CDU space and associated summary measures have distinct advantages to multiple domain comparisons, aiding
Strategic design of cost savings guarantee in energy performance contracting under uncertainty
International Nuclear Information System (INIS)
Deng, Qianli; Jiang, Xianglin; Cui, Qingbin; Zhang, Limao
2015-01-01
Highlights: • A methodology is proposed to assist Energy Service Companies to maintain competitiveness in winning bids. • Uncertainties within the energy cost savings are modeled stochastically using the Monte-Carlo simulation. • A strategic energy savings guarantee design curve is derived, where all points return as appropriate guarantees. • A campus case is presented to demonstrate the applicability for finding appropriate guaranteed savings value. - Abstract: Among the key barriers to profit in Energy Performance Contracting (EPC) are uncertainties about attaining the realized energy cost savings and potential disputes over the guaranteed cost savings. In this paper, a methodology has been proposed to assist the Energy Service Company (ESCO): (1) to evaluate the risk threshold if the guarantee has already been made, and (2) to determine the guarantee design, if the guarantee has not been made yet, that not only promises the ESCO’s profitability from EPC but also maintains its competitiveness to win the bid. Uncertainties within the energy cost savings are modeled stochastically using Monte-Carlo simulation, taking both the energy price fluctuation and the facility performance variability into account. Based on that, a strategic energy savings guarantee design curve is derived, that all the points on it would return as appropriate guarantees. Finally, a campus case is presented to demonstrate the applicability for finding the appropriate guaranteed savings value. This method is also worth popularizing in similar performance-based projects
Cost Recommendation under Uncertainty in IQWiG's Efficiency Frontier Framework.
Corro Ramos, Isaac; Lhachimi, Stefan K; Gerber-Grote, Andreas; Al, Maiwenn J
2017-02-01
The National Institute for Quality and Efficiency in Health Care (IQWiG) employs an efficiency frontier (EF) framework to facilitate setting maximum reimbursable prices for new interventions. Probabilistic sensitivity analysis (PSA) is used when yes/no reimbursement decisions are sought based on a fixed threshold. In the IQWiG framework, an additional layer of complexity arises as the EF itself may vary its shape in each PSA iteration, and thus the willingness-to-pay, indicated by the EF segments, may vary. To explore the practical problems arising when, within the EF approach, maximum reimbursable prices for new interventions are sought through PSA. When the EF is varied in a PSA, cost recommendations for new interventions may be determined by the mean or the median of the distances between each intervention's point estimate and each EF. Implications of using these metrics were explored in a simulation study based on the model used by IQWiG to assess the cost-effectiveness of 4 antidepressants. Depending on the metric used, cost recommendations can be contradictory. Recommendations based on the mean can also be inconsistent. Results (median) suggested that costs of duloxetine, venlafaxine, mirtazapine, and bupropion should be decreased by €131, €29, €12, and €99, respectively. These recommendations were implemented and the analysis repeated. New results suggested keeping the costs as they were. The percentage of acceptable PSA outcomes increased 41% on average, and the uncertainty associated to the net health benefit was significantly reduced. The median of the distances between every intervention outcome and every EF is a good proxy for the cost recommendation that would be given should the EF be fixed. Adjusting costs according to the median increased the probability of acceptance and reduced the uncertainty around the net health benefit distribution, resulting in a reduced uncertainty for decision makers.
Price setting under cost uncertainty and menu costs - the case of the Danish petrol market
International Nuclear Information System (INIS)
Stampe Christensen, M.
1994-01-01
This paper derives the optimal pricing policy for a firm facing menu costs and stochastic production cost. The pricing policy is a boundary pricing policy and numerical comparative static analysis shows how exogenous parameters - the drift and variance of the production cost, the discount factor and the menu costs - affect the boundaries. Analyzing daily data for the Danish petrol price illustrates that a boundary pricing policy indeed has been followed for the period 1988-1992, with occasional shifts in both the desired mark-up and more importantly in the width of the bounds. While the theoretical model can say nothing of the shifts in desired mark-up, changes in the width of the bounds are found to be consistent with the implications of the model. (au)
Cost reduction through system integration
International Nuclear Information System (INIS)
Helsing, P.
1994-01-01
In resent years cost reduction has been a key issue in the petroleum industry. Several findings are not economically attractive at the current cost level, and for this and other reasons some of the major oil companies require the suppliers to have implemented a cost reduction programme to prequalify for projects. The present paper addresses cost reduction through system design and integration in both product development and working methods. This is to be obtained by the combination of contracts by reducing unnecessary coordination and allow re-use of proven interface designs, improve subsystem integration by ''top down'' system design, and improve communication and exchange of experience. 3 figs
DEFF Research Database (Denmark)
Hao, Yin; Pizzol, Massimo; Xu, Linyu
2017-01-01
Some cities in China are facing serious air pollution problems including high concentrations of particles, SO2 and NOx. Exposure to PM2.5, one of the primary air pollutants in many cities in China, is highly correlated with various adverse health impacts and ultimately represents a cost for society....... The aim of this study is to assess health impacts and external costs related to PM2.5 pollution in Beijing, China with different baseline concentrations and valuation methods. The idea is to provide a reasonable estimate of the total health impacts and external cost due to PM2.5 pollution, as well...... as a quantification of the relevant uncertainty. PM2.5 concentrations were retrieved for the entire 2012 period in 16 districts of Beijing. The various PM2.5 related health impacts were identified and classified to avoid double counting. Exposure-response coefficients were then obtained from literature. Both...
A smart Monte Carlo procedure for production costing and uncertainty analysis
International Nuclear Information System (INIS)
Parker, C.; Stremel, J.
1996-01-01
Electric utilities using chronological production costing models to decide whether to buy or sell power over the next week or next few weeks need to determine potential profits or losses under a number of uncertainties. A large amount of money can be at stake--often $100,000 a day or more--and one party of the sale must always take on the risk. In the case of fixed price ($/MWh) contracts, the seller accepts the risk. In the case of cost plus contracts, the buyer must accept the risk. So, modeling uncertainty and understanding the risk accurately can improve the competitive edge of the user. This paper investigates an efficient procedure for representing risks and costs from capacity outages. Typically, production costing models use an algorithm based on some form of random number generator to select resources as available or on outage. These algorithms allow experiments to be repeated and gains and losses to be observed in a short time. The authors perform several experiments to examine the capability of three unit outage selection methods and measures their results. Specifically, a brute force Monte Carlo procedure, a Monte Carlo procedure with Latin Hypercube sampling, and a Smart Monte Carlo procedure with cost stratification and directed sampling are examined
Uncertainties in life cycle assessment of waste management systems
DEFF Research Database (Denmark)
Clavreul, Julie; Christensen, Thomas Højlund
2011-01-01
Life cycle assessment has been used to assess environmental performances of waste management systems in many studies. The uncertainties inherent to its results are often pointed out but not always quantified, which should be the case to ensure a good decisionmaking process. This paper proposes...... a method to assess all parameter uncertainties and quantify the overall uncertainty of the assessment. The method is exemplified in a case study, where the goal is to determine if anaerobic digestion of organic waste is more beneficial than incineration in Denmark, considering only the impact on global...... warming. The sensitivity analysis pointed out ten parameters particularly highly influencing the result of the study. In the uncertainty analysis, the distributions of these ten parameters were used in a Monte Carlo analysis, which concluded that incineration appeared more favourable than anaerobic...
Modeling multibody systems with uncertainties. Part II: Numerical applications
International Nuclear Information System (INIS)
Sandu, Corina; Sandu, Adrian; Ahmadian, Mehdi
2006-01-01
This study applies generalized polynomial chaos theory to model complex nonlinear multibody dynamic systems operating in the presence of parametric and external uncertainty. Theoretical and computational aspects of this methodology are discussed in the companion paper 'Modeling Multibody Dynamic Systems With Uncertainties. Part I: Theoretical and Computational Aspects .In this paper we illustrate the methodology on selected test cases. The combined effects of parametric and forcing uncertainties are studied for a quarter car model. The uncertainty distributions in the system response in both time and frequency domains are validated against Monte-Carlo simulations. Results indicate that polynomial chaos is more efficient than Monte Carlo and more accurate than statistical linearization. The results of the direct collocation approach are similar to the ones obtained with the Galerkin approach. A stochastic terrain model is constructed using a truncated Karhunen-Loeve expansion. The application of polynomial chaos to differential-algebraic systems is illustrated using the constrained pendulum problem. Limitations of the polynomial chaos approach are studied on two different test problems, one with multiple attractor points, and the second with a chaotic evolution and a nonlinear attractor set. The overall conclusion is that, despite its limitations, generalized polynomial chaos is a powerful approach for the simulation of multibody dynamic systems with uncertainties
Modeling multibody systems with uncertainties. Part II: Numerical applications
Energy Technology Data Exchange (ETDEWEB)
Sandu, Corina, E-mail: csandu@vt.edu; Sandu, Adrian; Ahmadian, Mehdi [Virginia Polytechnic Institute and State University, Mechanical Engineering Department (United States)
2006-04-15
This study applies generalized polynomial chaos theory to model complex nonlinear multibody dynamic systems operating in the presence of parametric and external uncertainty. Theoretical and computational aspects of this methodology are discussed in the companion paper 'Modeling Multibody Dynamic Systems With Uncertainties. Part I: Theoretical and Computational Aspects .In this paper we illustrate the methodology on selected test cases. The combined effects of parametric and forcing uncertainties are studied for a quarter car model. The uncertainty distributions in the system response in both time and frequency domains are validated against Monte-Carlo simulations. Results indicate that polynomial chaos is more efficient than Monte Carlo and more accurate than statistical linearization. The results of the direct collocation approach are similar to the ones obtained with the Galerkin approach. A stochastic terrain model is constructed using a truncated Karhunen-Loeve expansion. The application of polynomial chaos to differential-algebraic systems is illustrated using the constrained pendulum problem. Limitations of the polynomial chaos approach are studied on two different test problems, one with multiple attractor points, and the second with a chaotic evolution and a nonlinear attractor set. The overall conclusion is that, despite its limitations, generalized polynomial chaos is a powerful approach for the simulation of multibody dynamic systems with uncertainties.
Shimansky, Y P
2011-05-01
It is well known from numerous studies that perception can be significantly affected by intended action in many everyday situations, indicating that perception and related decision-making is not a simple, one-way sequence, but a complex iterative cognitive process. However, the underlying functional mechanisms are yet unclear. Based on an optimality approach, a quantitative computational model of one such mechanism has been developed in this study. It is assumed in the model that significant uncertainty about task-related parameters of the environment results in parameter estimation errors and an optimal control system should minimize the cost of such errors in terms of the optimality criterion. It is demonstrated that, if the cost of a parameter estimation error is significantly asymmetrical with respect to error direction, the tendency to minimize error cost creates a systematic deviation of the optimal parameter estimate from its maximum likelihood value. Consequently, optimization of parameter estimate and optimization of control action cannot be performed separately from each other under parameter uncertainty combined with asymmetry of estimation error cost, thus making the certainty equivalence principle non-applicable under those conditions. A hypothesis that not only the action, but also perception itself is biased by the above deviation of parameter estimate is supported by ample experimental evidence. The results provide important insights into the cognitive mechanisms of interaction between sensory perception and planning an action under realistic conditions. Implications for understanding related functional mechanisms of optimal control in the CNS are discussed.
Video distribution system cost model
Gershkoff, I.; Haspert, J. K.; Morgenstern, B.
1980-01-01
A cost model that can be used to systematically identify the costs of procuring and operating satellite linked communications systems is described. The user defines a network configuration by specifying the location of each participating site, the interconnection requirements, and the transmission paths available for the uplink (studio to satellite), downlink (satellite to audience), and voice talkback (between audience and studio) segments of the network. The model uses this information to calculate the least expensive signal distribution path for each participating site. Cost estimates are broken downy by capital, installation, lease, operations and maintenance. The design of the model permits flexibility in specifying network and cost structure.
Generalization of uncertainty relation for quantum and stochastic systems
Koide, T.; Kodama, T.
2018-06-01
The generalized uncertainty relation applicable to quantum and stochastic systems is derived within the stochastic variational method. This relation not only reproduces the well-known inequality in quantum mechanics but also is applicable to the Gross-Pitaevskii equation and the Navier-Stokes-Fourier equation, showing that the finite minimum uncertainty between the position and the momentum is not an inherent property of quantum mechanics but a common feature of stochastic systems. We further discuss the possible implication of the present study in discussing the application of the hydrodynamic picture to microscopic systems, like relativistic heavy-ion collisions.
International Nuclear Information System (INIS)
Cai, Y.P.; Huang, G.H.; Yang, Z.F.; Tan, Q.
2009-01-01
Management of energy resources is crucial for many regions throughout the world. Many economic, environmental and political factors are having significant effects on energy management practices, leading to a variety of uncertainties in relevant decision making. The objective of this research is to identify optimal strategies in the planning of energy management systems under multiple uncertainties through the development of a fuzzy-random interval programming (FRIP) model. The method is based on an integration of the existing interval linear programming (ILP), superiority-inferiority-based fuzzy-stochastic programming (SI-FSP) and mixed integer linear programming (MILP). Such a FRIP model allows multiple uncertainties presented as interval values, possibilistic and probabilistic distributions, as well as their combinations within a general optimization framework. It can also be used for facilitating capacity-expansion planning of energy-production facilities within a multi-period and multi-option context. Complexities in energy management systems can be systematically reflected, thus applicability of the modeling process can be highly enhanced. The developed method has then been applied to a case of long-term energy management planning for a region with three cities. Useful solutions for the planning of energy management systems were generated. Interval solutions associated with different risk levels of constraint violation were obtained. They could be used for generating decision alternatives and thus help decision makers identify desired policies under various economic and system-reliability constraints. The solutions can also provide desired energy resource/service allocation and capacity-expansion plans with a minimized system cost, a maximized system reliability and a maximized energy security. Tradeoffs between system costs and constraint-violation risks could be successfully tackled, i.e., higher costs will increase system stability, while a desire for lower
Assessing Power System Stability Following Load Changes and Considering Uncertainty
Directory of Open Access Journals (Sweden)
D. V. Ngo
2018-04-01
Full Text Available An increase in load capacity during the operation of a power system usually causes voltage drop and leads to system instability, so it is necessary to monitor the effect of load changes. This article presents a method of assessing the power system stability according to the load node capacity considering uncertainty factors in the system. The proposed approach can be applied to large-scale power systems for voltage stability assessment in real-time.
Estimation of Model Uncertainties in Closed-loop Systems
DEFF Research Database (Denmark)
Niemann, Hans Henrik; Poulsen, Niels Kjølstad
2008-01-01
This paper describe a method for estimation of parameters or uncertainties in closed-loop systems. The method is based on an application of the dual YJBK (after Youla, Jabr, Bongiorno and Kucera) parameterization of all systems stabilized by a given controller. The dual YJBK transfer function...
Li, Y P; Huang, G H
2010-09-15
Considerable public concerns have been raised in the past decades since a large amount of pollutant emissions from municipal solid waste (MSW) disposal of processes pose risks on surrounding environment and human health. Moreover, in MSW management, various uncertainties exist in the related costs, impact factors and objectives, which can affect the optimization processes and the decision schemes generated. In this study, an interval-based possibilistic programming (IBPP) method is developed for planning the MSW management with minimized system cost and environmental impact under uncertainty. The developed method can deal with uncertainties expressed as interval values and fuzzy sets in the left- and right-hand sides of constraints and objective function. An interactive algorithm is provided for solving the IBPP problem, which does not lead to more complicated intermediate submodels and has a relatively low computational requirement. The developed model is applied to a case study of planning a MSW management system, where mixed integer linear programming (MILP) technique is introduced into the IBPP framework to facilitate dynamic analysis for decisions of timing, sizing and siting in terms of capacity expansion for waste-management facilities. Three cases based on different waste-management policies are examined. The results obtained indicate that inclusion of environmental impacts in the optimization model can change the traditional waste-allocation pattern merely based on the economic-oriented planning approach. The results obtained can help identify desired alternatives for managing MSW, which has advantages in providing compromised schemes under an integrated consideration of economic efficiency and environmental impact under uncertainty. Copyright 2010 Elsevier B.V. All rights reserved.
Sensitivity of nuclear fuel-cycle cost to uncertainties in nuclear data. Final report
International Nuclear Information System (INIS)
Becker, M.; Harris, D.R.
1980-11-01
An improved capability for assessing the economic implications of uncertainties in nuclear data and methods on the power reactor fuel cycle was developed. This capability is applied to the sensitivity analysis of fuel-cycle cost with respect to changes in nuclear data and related computational methods. Broad group sensitivities for both a typical BWR and a PWR are determined under the assumption of a throwaway fuel cycle as well as for a scenario under which reprocessing is allowed. Particularly large dollar implications are found for the thermal and resonance cross sections of fissile and fertile materials. Sensitivities for the throwaway case are found to be significantly larger than for the recycle case. Constrained sensitivities obtained for cases in which information from critical experiments or other benchmarks is used in the design calculation to adjust a parameter such as anti ν are compared with unconstrained sensitivities. Sensitivities of various alternate fuel cycles were examined. These included the extended-burnup (18-month) LWR cycle, the mixed-oxide (plutonium) cycle, uranium-thorium and denatured uranium-thorium cycles, as well as CANDU-type reactor cycles. The importance of the thermal capture and fission cross sections of 239 Pu is shown to be very large in all cases. Detailed, energy dependent sensitivity profiles are provided for the thermal range (below 1.855 eV). Finally, sensitivity coefficients are combined with data uncertainties to determine the impact of such uncertainties on fuel-cycle cost parameters
A statistical view of uncertainty in expert systems
International Nuclear Information System (INIS)
Spiegelhalter, D.J.
1986-01-01
The constructors of expert systems interpret ''uncertainty'' in a wide sense and have suggested a variety of qualitative and quantitative techniques for handling the concept, such as the theory of ''endorsements,'' fuzzy reasoning, and belief functions. After a brief selective review of procedures that do not adhere to the laws of probability, it is argued that a subjectivist Bayesian view of uncertainty, if flexibly applied, can provide many of the features demanded by expert systems. This claim is illustrated with a number of examples of probabilistic reasoning, and a connection drawn with statistical work on the graphical representation of multivariate distributions. Possible areas of future research are outlined
Robust Performance of Systems with Structured Uncertainties in State Space
DEFF Research Database (Denmark)
Zhou, Kemin; Khargonekar, Pramod P.; Stoustrup, Jakob
1995-01-01
This paper considers robust performance analysis and state feedback design for systems with time-varying parameter uncertainties. The notion of a strongly robust % performance criterion is introduced, and its applications in robust performance analysis and synthesis for nominally linear systems...... with time-varying uncertainties are discussed and compared with the constant scaled small gain criterion. It is shown that most robust performance analysis and synthesis problems under this strongly robust % performance criterion can be transformed into linear matrix inequality problems, and can be solved...
International Nuclear Information System (INIS)
Chernyavs'ka, Liliya; Gulli, Francesco
2010-01-01
In this paper, we attempt to measure the environmental benefits of hydrogen deployment in the transportation sector. We compare the hydrogen pathways to the conventional transportation fuel cycles in terms of external costs, estimated using the results of the most accurate methodologies available in this field. The central values of performed analysis bring us ambiguous results. The external cost of the best conventional solution ('oil to diesel hybrid internal-combustion engine') in some cases is just higher and in others just lower than that of the best fossil fuel to hydrogen solution ('natural gas to hydrogen fuel cell'). Nevertheless, by accounting for the uncertainty about external costs, we are able to remove this ambiguity highlighting that the hydrogen pathway provides significant environmental benefits ,especially in densely populated areas, assuming 100% city driving.
Advanced Concepts in Fuzzy Logic and Systems with Membership Uncertainty
Starczewski, Janusz T
2013-01-01
This book generalizes fuzzy logic systems for different types of uncertainty, including - semantic ambiguity resulting from limited perception or lack of knowledge about exact membership functions - lack of attributes or granularity arising from discretization of real data - imprecise description of membership functions - vagueness perceived as fuzzification of conditional attributes. Consequently, the membership uncertainty can be modeled by combining methods of conventional and type-2 fuzzy logic, rough set theory and possibility theory. In particular, this book provides a number of formulae for implementing the operation extended on fuzzy-valued fuzzy sets and presents some basic structures of generalized uncertain fuzzy logic systems, as well as introduces several of methods to generate fuzzy membership uncertainty. It is desirable as a reference book for under-graduates in higher education, master and doctor graduates in the courses of computer science, computational intelligence, or...
Ren, Jingzheng; Dong, Liang; Sun, Lu; Goodsite, Michael Evan; Tan, Shiyu; Dong, Lichun
2015-01-01
The aim of this work was to develop a model for optimizing the life cycle cost of biofuel supply chain under uncertainties. Multiple agriculture zones, multiple transportation modes for the transport of grain and biofuel, multiple biofuel plants, and multiple market centers were considered in this model, and the price of the resources, the yield of grain and the market demands were regarded as interval numbers instead of constants. An interval linear programming was developed, and a method for solving interval linear programming was presented. An illustrative case was studied by the proposed model, and the results showed that the proposed model is feasible for designing biofuel supply chain under uncertainties. Copyright © 2015 Elsevier Ltd. All rights reserved.
Costing systems design for sustainability
Directory of Open Access Journals (Sweden)
Mihaela TURTUREA
2013-10-01
Full Text Available The aim of this article is to present an overall image of the way Accounting responds to nowadays user’s needs in relation to the quantification of the impact companies have towards the environment. Regarding this, there have been analyzed concepts like sustainable development, environmental accounting, environmental costs and there have been presented the main progress towards environmental cost identification and measurement from the perspective of Activity Based Costing system. To provide an overall image of this concepts, there have been used as research methodology methods the documentation from literature review, analysis, synthesis and comparison.
Deep uncertainty and broad heterogeneity in country-level social cost of carbon
Ricke, K.; Drouet, L.; Caldeira, K.; Tavoni, M.
2017-12-01
The social cost of carbon (SCC) is a commonly employed metric of the expected economic damages expected from carbon dioxide (CO2) emissions. Recent estimates of SCC range from approximately 10/tonne of CO2 to as much as 1000/tCO2, but these have been computed at the global level. While useful in an optimal policy context, a world-level approach obscures the heterogeneous geography of climate damages and vast differences in country-level contributions to global SCC, as well as climate and socio-economic uncertainties, which are much larger at the regional level. For the first time, we estimate country-level contributions to SCC using recent climate and carbon-cycle model projections, empirical climate-driven economic damage estimations, and information from the Shared Socio-economic Pathways. Central specifications show high global SCC values (median: 417 /tCO2, 66% confidence intervals: 168 - 793 /tCO2) with country-level contributions ranging from -11 (-8 - -14) /tCO2 to 86 (50 - 158) /tCO2. We quantify climate-, scenario- and economic damage- driven uncertainties associated with the calculated values of SCC. We find that while the magnitude of country-level social cost of carbon is highly uncertain, the relative positioning among countries is consistent. Countries incurring large fractions of the global cost include India, China, and the United States. The share of SCC distributed among countries is robust, indicating climate change winners and losers from a geopolitical perspective.
A game-theoretic approach for calibration of low-cost magnetometers under noise uncertainty
Siddharth, S.; Ali, A. S.; El-Sheimy, N.; Goodall, C. L.; Syed, Z. F.
2012-02-01
Pedestrian heading estimation is a fundamental challenge in Global Navigation Satellite System (GNSS)-denied environments. Additionally, the heading observability considerably degrades in low-speed mode of operation (e.g. walking), making this problem even more challenging. The goal of this work is to improve the heading solution when hand-held personal/portable devices, such as cell phones, are used for positioning and to improve the heading estimation in GNSS-denied signal environments. Most smart phones are now equipped with self-contained, low cost, small size and power-efficient sensors, such as magnetometers, gyroscopes and accelerometers. A magnetometer needs calibration before it can be properly employed for navigation purposes. Magnetometers play an important role in absolute heading estimation and are embedded in many smart phones. Before the users navigate with the phone, a calibration is invoked to ensure an improved signal quality. This signal is used later in the heading estimation. In most of the magnetometer-calibration approaches, the motion modes are seldom described to achieve a robust calibration. Also, suitable calibration approaches fail to discuss the stopping criteria for calibration. In this paper, the following three topics are discussed in detail that are important to achieve proper magnetometer-calibration results and in turn the most robust heading solution for the user while taking care of the device misalignment with respect to the user: (a) game-theoretic concepts to attain better filter parameter tuning and robustness in noise uncertainty, (b) best maneuvers with focus on 3D and 2D motion modes and related challenges and (c) investigation of the calibration termination criteria leveraging the calibration robustness and efficiency.
A game-theoretic approach for calibration of low-cost magnetometers under noise uncertainty
International Nuclear Information System (INIS)
Siddharth, S; Ali, A S; El-Sheimy, N; Goodall, C L; Syed, Z F
2012-01-01
Pedestrian heading estimation is a fundamental challenge in Global Navigation Satellite System (GNSS)-denied environments. Additionally, the heading observability considerably degrades in low-speed mode of operation (e.g. walking), making this problem even more challenging. The goal of this work is to improve the heading solution when hand-held personal/portable devices, such as cell phones, are used for positioning and to improve the heading estimation in GNSS-denied signal environments. Most smart phones are now equipped with self-contained, low cost, small size and power-efficient sensors, such as magnetometers, gyroscopes and accelerometers. A magnetometer needs calibration before it can be properly employed for navigation purposes. Magnetometers play an important role in absolute heading estimation and are embedded in many smart phones. Before the users navigate with the phone, a calibration is invoked to ensure an improved signal quality. This signal is used later in the heading estimation. In most of the magnetometer-calibration approaches, the motion modes are seldom described to achieve a robust calibration. Also, suitable calibration approaches fail to discuss the stopping criteria for calibration. In this paper, the following three topics are discussed in detail that are important to achieve proper magnetometer-calibration results and in turn the most robust heading solution for the user while taking care of the device misalignment with respect to the user: (a) game-theoretic concepts to attain better filter parameter tuning and robustness in noise uncertainty, (b) best maneuvers with focus on 3D and 2D motion modes and related challenges and (c) investigation of the calibration termination criteria leveraging the calibration robustness and efficiency. (paper)
Directory of Open Access Journals (Sweden)
Gurkan eSin
2015-02-01
Full Text Available Capital investment, next to the product demand, sales and production costs, is one of the key metrics commonly used for project evaluation and feasibility assessment. Estimating the investment costs of a new product/process alternative during early stage design is a challenging task. This is especially important in biorefinery research, where available information and experiences with new technologies is limited. A systematic methodology for uncertainty analysis of cost data is proposed that employs (a Bootstrapping as a regression method when cost data is available and (b the Monte Carlo technique as an error propagation method based on expert input when cost data is not available. Four well-known models for early stage cost estimation are reviewed an analyzed using the methodology. The significance of uncertainties of cost data for early stage process design is highlighted using the synthesis and design of a biorefinery as a case study. The impact of uncertainties in cost estimation on the identification of optimal processing paths is found to be profound. To tackle this challenge, a comprehensive techno-economic risk analysis framework is presented to enable robust decision making under uncertainties. One of the results using an order-of-magnitude estimate shows that the production of diethyl ether and 1,3-butadiene are the most promising with economic risks of 0.24 MM$/a and 4.6 MM$/a due to uncertainties in cost estimations, respectively.
Uncertainty analysis of a nondestructive radioassay system for transuranic waste
International Nuclear Information System (INIS)
Harker, Y.D.; Blackwood, L.G.; Meachum, T.R.; Yoon, W.Y.
1996-01-01
Radioassay of transuranic waste in 207 liter drums currently stored at the Idaho National Engineering Laboratory is achieved using a Passive Active Neutron (PAN) nondestructive assay system. In order to meet data quality assurance requirements for shipping and eventual permanent storage of these drums at the Waste Isolation Pilot Plant in Carlsbad, New Mexico, the total uncertainty of the PAN system measurements must be assessed. In particular, the uncertainty calculations are required to include the effects of variations in waste matrix parameters and related variables on the final measurement results. Because of the complexities involved in introducing waste matrix parameter effects into the uncertainty calculations, standard methods of analysis (e.g., experimentation followed by propagation of errors) could not be implemented. Instead, a modified statistical sampling and verification approach was developed. In this modified approach the total performance of the PAN system is simulated using computer models of the assay system and the resultant output is compared with the known input to assess the total uncertainty. This paper describes the simulation process and illustrates its application to waste comprised of weapons grade plutonium-contaminated graphite molds
Groundwater detection monitoring system design under conditions of uncertainty
Yenigül, N.B.
2006-01-01
Landfills represent a wide-spread and significant threat to groundwater quality. In this thesis a methodology was developed for the design of optimal groundwater moni-toring system design at landfill sites under conditions of uncertainty. First a decision analysis approach was presented for optimal
Uncertainty in prediction and simulation of flow in sewer systems
DEFF Research Database (Denmark)
Breinholt, Anders
the uncertainty in the state variables. Additionally the observation noise is accounted for by a separate observation noise term. This approach is also referred to as stochastic grey-box modelling. A state dependent diffusion term was developed using a Lamperti transformation of the states, and implemented...... performance beyond the one-step. The reliability was satisfied for the one-step prediction but were increasingly biased as the prediction horizon was expanded, particularly in rainy periods. GLUE was applied for estimating uncertainty in such a way that the selection of behavioral parameter sets continued....... Conversely the parameter estimates of the stochastic approach are physically meaningful. This thesis has contributed to developing simplified rainfall-runoff models that are suitable for model predictive control of urban drainage systems that takes uncertainty into account....
Energy Technology Data Exchange (ETDEWEB)
Puustinen, H.; Aunela-Tapola, L.; Tolvanen, M.; Vahlman, T. [VTT Chemical Technology, Espoo (Finland). Environmental Technology; Kovanen, K. [VTT Building Technology, Espoo (Finland). Building Physics, Building Services and Fire Technology
1999-09-01
This report presents a procedure to determine the uncertainty of an automated emission measuring system (AMS) by comparing the results with a second method (REF). The procedure determines the uncertainty of AMS by comparing the final concentration and emission results of AMS and REF. In this way, the data processing of the plant is included in the result evaluation. This procedure assumes that the uncertainty of REF is known and determined in due form. The uncertainty determination has been divided into two cases; varying and nearly constant concentration. The suggested procedure calculates the uncertainty of AMS at the 95 % confidence level by a tabulated t-value. A minimum of three data pairs is required. However, a higher amount of data pairs is desirable, since a low amount of data pairs results in a higher uncertainty of AMS. The uncertainty of AMS is valid only within the range of concentrations at which the tests were carried out. Statistical data processing shows that the uncertainty of the reference method has a significant effect on the uncertainty of AMS, which always becomes larger than the uncertainty of REF. This should be taken into account when testing whether AMS fulfils the given uncertainty limits. Practical details, concerning parallel measurements at the plant, and the costs of the measurement campaign, have been taken into account when suggesting alternative ways for implementing the comparative measurements. (orig.) 6 refs.
Certainty Equivalence M-MRAC for Systems with Unmatched Uncertainties
Stepanyan, Vahram; Krishnakumar, Kalmanje
2012-01-01
The paper presents a certainty equivalence state feedback indirect adaptive control design method for the systems of any relative degree with unmatched uncertainties. The approach is based on the parameter identification (estimation) model, which is completely separated from the control design and is capable of producing parameter estimates as fast as the computing power allows without generating high frequency oscillations. It is shown that the system's input and output tracking errors can be systematically decreased by the proper choice of the design parameters.
Modifications to Replacement Costs System
International Nuclear Information System (INIS)
Godec, M.
1989-01-01
The purpose of this memorandum is to document the improvements and modifications made to the Replacement Costs of Crude Oil (REPCO) Supply Analysis System. While some of this work was performed under our previous support contract to DOE/ASFE, we are presenting all modifications and improvements are presented here for completeness. The memo primarily documents revisions made to the Lower-48 Onshore Model. Revisions and modifications made to other components and models in the REPCO system which are documented elsewhere are only highlighted in this memo. Generally, the modifications made to the Lower-48 Onshore Model reflect changes that have occurred in domestic drilling, oil field costs, and reserves since 1982, the date of the most recent available data used for the original Replacement Costs report, published in 1985
Evaluation of uncertainty in dosimetry of irradiator system
International Nuclear Information System (INIS)
Santos, Gelson P.; Potiens, Maria P.A.; Vivolo, Vitor
2005-01-01
This paper describes the study of uncertainties in the estimates of dosimetry irradiator system STS 0B85 of LCI IPEN/CNEN-SP. This study is relevant for determination of best measurement capability when the laboratory performs routine calibrations of measuring radiation next the optimal measures designed to radioprotection. It is also a requirement for obtaining the accreditation of the laboratory by the INMETRO. For this dosimetry was used a reference system of the laboratory composed of a electrometer and a spherical ionization chamber of 1 liter. Measurements were made at five distances selected so to include the whole range of the optical bench tests and using three attenuators filters so as to extend the measurement capability. The magnitude used for evaluation was the rate of air kerma for 1 37C s and 6 0C o beams. Were carried out four series of measurements. It was verified the inverse square law to these series and their sets of uncertainty. Unfiltered, with one and two filters series showed good agreement with the inverse square low and the maximum uncertainty obtained was approximately 1.7%. In series with all the filters was a major deviation of the inverse square law and wide increase in uncertainty to measurements at the end of the optical bench
(Value Stream Costing As A New Costing System)
Karcıoğlu, Reşar; Nuray, Meral
2010-01-01
In recent years, the number of lean company which use lean manufacturing system is rising. This companies use the standard costing while appropriate for traditional bathch manufacturing. But standard costing system fails to support the goals of lean manufacturing system. A different method of costing based upon the characteristics of the value stream is needed to fulfill the needs of the lean company. This systemis Value Stream Costing. When a lean company moves to value stream management, th...
Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty
Nguyen, Nhan T.
2012-01-01
This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.
Reliability assessment of complex electromechanical systems under epistemic uncertainty
International Nuclear Information System (INIS)
Mi, Jinhua; Li, Yan-Feng; Yang, Yuan-Jian; Peng, Weiwen; Huang, Hong-Zhong
2016-01-01
The appearance of macro-engineering and mega-project have led to the increasing complexity of modern electromechanical systems (EMSs). The complexity of the system structure and failure mechanism makes it more difficult for reliability assessment of these systems. Uncertainty, dynamic and nonlinearity characteristics always exist in engineering systems due to the complexity introduced by the changing environments, lack of data and random interference. This paper presents a comprehensive study on the reliability assessment of complex systems. In view of the dynamic characteristics within the system, it makes use of the advantages of the dynamic fault tree (DFT) for characterizing system behaviors. The lifetime of system units can be expressed as bounded closed intervals by incorporating field failures, test data and design expertize. Then the coefficient of variation (COV) method is employed to estimate the parameters of life distributions. An extended probability-box (P-Box) is proposed to convey the present of epistemic uncertainty induced by the incomplete information about the data. By mapping the DFT into an equivalent Bayesian network (BN), relevant reliability parameters and indexes have been calculated. Furthermore, the Monte Carlo (MC) simulation method is utilized to compute the DFT model with consideration of system replacement policy. The results show that this integrated approach is more flexible and effective for assessing the reliability of complex dynamic systems. - Highlights: • A comprehensive study on the reliability assessment of complex system is presented. • An extended probability-box is proposed to convey the present of epistemic uncertainty. • The dynamic fault tree model is built. • Bayesian network and Monte Carlo simulation methods are used. • The reliability assessment of a complex electromechanical system is performed.
Risk classification and uncertainty propagation for virtual water distribution systems
International Nuclear Information System (INIS)
Torres, Jacob M.; Brumbelow, Kelly; Guikema, Seth D.
2009-01-01
While the secrecy of real water distribution system data is crucial, it poses difficulty for research as results cannot be publicized. This data includes topological layouts of pipe networks, pump operation schedules, and water demands. Therefore, a library of virtual water distribution systems can be an important research tool for comparative development of analytical methods. A virtual city, 'Micropolis', has been developed, including a comprehensive water distribution system, as a first entry into such a library. This virtual city of 5000 residents is fully described in both geographic information systems (GIS) and EPANet hydraulic model frameworks. A risk classification scheme and Monte Carlo analysis are employed for an attempted water supply contamination attack. Model inputs to be considered include uncertainties in: daily water demand, seasonal demand, initial storage tank levels, the time of day a contamination event is initiated, duration of contamination event, and contaminant quantity. Findings show that reasonable uncertainties in model inputs produce high variability in exposure levels. It is also shown that exposure level distributions experience noticeable sensitivities to population clusters within the contaminant spread area. High uncertainties in exposure patterns lead to greater resources needed for more effective mitigation strategies.
Cost Estimation and Control for Flight Systems
Hammond, Walter E.; Vanhook, Michael E. (Technical Monitor)
2002-01-01
Good program management practices, cost analysis, cost estimation, and cost control for aerospace flight systems are interrelated and depend upon each other. The best cost control process cannot overcome poor design or poor systems trades that lead to the wrong approach. The project needs robust Technical, Schedule, Cost, Risk, and Cost Risk practices before it can incorporate adequate Cost Control. Cost analysis both precedes and follows cost estimation -- the two are closely coupled with each other and with Risk analysis. Parametric cost estimating relationships and computerized models are most often used. NASA has learned some valuable lessons in controlling cost problems, and recommends use of a summary Project Manager's checklist as shown here.
Groves, Curtis Edward
2014-01-01
Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This paper describes an approach to quantify the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft without the use of test data. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional "validation by test only" mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions. Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computational Fluid Dynamics can be used to verify these requirements; however, the model must be validated by test data. This research includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available and open source solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT, STARCCM+, and OPENFOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid Dynamics model using the methodology found in "Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations". This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics
Groves, Curtis Edward
2014-01-01
Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This paper describes an approach to quantify the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft without the use of test data. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional validation by test only mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions.Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computational Fluid Dynamics can be used to verify these requirements; however, the model must be validated by test data. This research includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available and open source solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT, STARCCM+, and OPENFOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid Dynamics model using the methodology found in Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations. This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics predictions
Stochastic Control Synthesis of Systems with Structured Uncertainty
Padula, Sharon L. (Technical Monitor); Crespo, Luis G.
2003-01-01
This paper presents a study on the design of robust controllers by using random variables to model structured uncertainty for both SISO and MIMO feedback systems. Once the parameter uncertainty is prescribed with probability density functions, its effects are propagated through the analysis leading to stochastic metrics for the system's output. Control designs that aim for satisfactory performances while guaranteeing robust closed loop stability are attained by solving constrained non-linear optimization problems in the frequency domain. This approach permits not only to quantify the probability of having unstable and unfavorable responses for a particular control design but also to search for controls while favoring the values of the parameters with higher chance of occurrence. In this manner, robust optimality is achieved while the characteristic conservatism of conventional robust control methods is eliminated. Examples that admit closed form expressions for the probabilistic metrics of the output are used to elucidate the nature of the problem at hand and validate the proposed formulations.
Formal modeling of a system of chemical reactions under uncertainty.
Ghosh, Krishnendu; Schlipf, John
2014-10-01
We describe a novel formalism representing a system of chemical reactions, with imprecise rates of reactions and concentrations of chemicals, and describe a model reduction method, pruning, based on the chemical properties. We present two algorithms, midpoint approximation and interval approximation, for construction of efficient model abstractions with uncertainty in data. We evaluate computational feasibility by posing queries in computation tree logic (CTL) on a prototype of extracellular-signal-regulated kinase (ERK) pathway.
International Nuclear Information System (INIS)
Cheali, Peam; Gernaey, Krist V.; Sin, Gürkan
2015-01-01
Capital investment, next to the product demand, sales, and production costs, is one of the key metrics commonly used for project evaluation and feasibility assessment. Estimating the investment costs of a new product/process alternative during early-stage design is a challenging task, which is especially relevant in biorefinery research where information about new technologies and experience with new technologies is limited. A systematic methodology for uncertainty analysis of cost data is proposed that employs: (a) bootstrapping as a regression method when cost data are available; and, (b) the Monte Carlo technique as an error propagation method based on expert input when cost data are not available. Four well-known models for early-stage cost estimation are reviewed and analyzed using the methodology. The significance of uncertainties of cost data for early-stage process design is highlighted using the synthesis and design of a biorefinery as a case study. The impact of uncertainties in cost estimation on the identification of optimal processing paths is indeed found to be profound. To tackle this challenge, a comprehensive techno-economic risk analysis framework is presented to enable robust decision-making under uncertainties. One of the results using order-of-magnitude estimates shows that the production of diethyl ether and 1,3-butadiene are the most promising with the lowest economic risks (among the alternatives considered) of 0.24 MM$/a and 4.6 MM$/a, respectively.
Energy Technology Data Exchange (ETDEWEB)
Cheali, Peam; Gernaey, Krist V.; Sin, Gürkan, E-mail: gsi@kt.dtu.dk [Department of Chemical and Biochemical Engineering, Technical University of Denmark, Lyngby (Denmark)
2015-02-06
Capital investment, next to the product demand, sales, and production costs, is one of the key metrics commonly used for project evaluation and feasibility assessment. Estimating the investment costs of a new product/process alternative during early-stage design is a challenging task, which is especially relevant in biorefinery research where information about new technologies and experience with new technologies is limited. A systematic methodology for uncertainty analysis of cost data is proposed that employs: (a) bootstrapping as a regression method when cost data are available; and, (b) the Monte Carlo technique as an error propagation method based on expert input when cost data are not available. Four well-known models for early-stage cost estimation are reviewed and analyzed using the methodology. The significance of uncertainties of cost data for early-stage process design is highlighted using the synthesis and design of a biorefinery as a case study. The impact of uncertainties in cost estimation on the identification of optimal processing paths is indeed found to be profound. To tackle this challenge, a comprehensive techno-economic risk analysis framework is presented to enable robust decision-making under uncertainties. One of the results using order-of-magnitude estimates shows that the production of diethyl ether and 1,3-butadiene are the most promising with the lowest economic risks (among the alternatives considered) of 0.24 MM$/a and 4.6 MM$/a, respectively.
State Estimation for Sensor Monitoring System with Uncertainty and Disturbance
Directory of Open Access Journals (Sweden)
Jianhong Sun
2014-10-01
Full Text Available This paper considers the state estimation problem for the sensor monitoring system which contains system uncertainty and nonlinear disturbance. In the sensor monitoring system, states of each inner sensor node usually contains system uncertainty, and external noise often works as nonlinear item. Besides, information transmission in the system is also time consuming. All mentioned above may arouse in unstable of the monitoring system. In this case, states of sensors could be wrongly sampled. Under this circumstance, a proper mathematical model is proposed and by the use of Lipschitz condition, the nonlinear item is transformed to linear one. In addition, we suppose that all sensor nodes are distributed arranged, no interface occurs with each other. By establishing proper Lyapunov– Krasovskii functional, sufficient conditions are acquired by solving linear matrix inequality to make the error augmented system stable, and the gains of observers are also derived. Finally, an illustrated example is given to show that system observed value tracks system states well, which fully demonstrate the effectiveness of our result.
Hunink, Maria; Bult, J.R.; De Vries, J; Weinstein, MC
1998-01-01
Purpose. To illustrate the use of a nonparametric bootstrap method in the evaluation of uncertainty in decision models analyzing cost-effectiveness. Methods. The authors reevaluated a previously published cost-effectiveness analysis that used a Markov model comparing initial percutaneous
McMillan, Hilary; Seibert, Jan; Petersen-Overleir, Asgeir; Lang, Michel; White, Paul; Snelder, Ton; Rutherford, Kit; Krueger, Tobias; Mason, Robert; Kiang, Julie
2017-07-01
Streamflow data are used for important environmental and economic decisions, such as specifying and regulating minimum flows, managing water supplies, and planning for flood hazards. Despite significant uncertainty in most flow data, the flow series for these applications are often communicated and used without uncertainty information. In this commentary, we argue that proper analysis of uncertainty in river flow data can reduce costs and promote robust conclusions in water management applications. We substantiate our argument by providing case studies from Norway and New Zealand where streamflow uncertainty analysis has uncovered economic costs in the hydropower industry, improved public acceptance of a controversial water management policy, and tested the accuracy of water quality trends. We discuss the need for practical uncertainty assessment tools that generate multiple flow series realizations rather than simple error bounds. Although examples of such tools are in development, considerable barriers for uncertainty analysis and communication still exist for practitioners, and future research must aim to provide easier access and usability of uncertainty estimates. We conclude that flow uncertainty analysis is critical for good water management decisions.
Sustainable infrastructure system modeling under uncertainties and dynamics
Huang, Yongxi
potential risks caused by feedstock seasonality and demand uncertainty. Facility spatiality, time variation of feedstock yields, and demand uncertainty are integrated into a two-stage stochastic programming (SP) framework. In the study of Transitional Energy System Modeling under Uncertainty, a multistage stochastic dynamic programming is established to optimize the process of building and operating fuel production facilities during the transition. Dynamics due to the evolving technologies and societal changes and uncertainty due to demand fluctuations are the major issues to be addressed.
Linear collider systems and costs
International Nuclear Information System (INIS)
Loew, G.A.
1993-05-01
The purpose of this paper is to examine some of the systems and sub-systems involved in so-called ''conventional'' e + e - linear colliders and to study how their design affects the overall cost of these machines. There are presently a total of at least six 500 GeV c. of m. linear collider projects under study in the world. Aside from TESLA (superconducting linac at 1.3 GHz) and CLIC (two-beam accelerator with main linac at 30GHz), the other four proposed e + e - linear colliders can be considered ''conventional'' in that their main linacs use the proven technique of driving room temperature accelerator sections with pulsed klystrons and modulators. The centrally distinguishing feature between these projects is their main linac rf frequency: 3 GHz for the DESY machine, 11.424 GHz for the SLAC and JLC machines, and 14 GHz for the VLEPP machine. The other systems, namely the electron and positron sources, preaccelerators, compressors, damping rings and final foci, are fairly similar from project to project. Probably more than 80% of the cost of these linear colliders will be incurred in the two main linacs facing each other and it is therefore in their design and construction that major savings or extra costs may be found
Electric-power systems planning and greenhouse-gas emission management under uncertainty
International Nuclear Information System (INIS)
Li, Y.P.; Huang, G.H.
2012-01-01
Highlight: ►A multistage stochastic integer programming model is developed for planning electric-power systems. ►Uncertain and dynamic information can be incorporated within a multilayer scenario tree. ►This can help minimize system cost under random energy demand and greenhouse gas (GHG) abatement goal. ►Results can support decisions of facility expansion, electricity supply and GHG mitigation. - Abstract: In this study, a multistage interval-stochastic integer programming model is formulated for managing greenhouse gas (GHG) emissions and planning electric-power systems under uncertainty. The developed model can reflect dynamic, interactive, and uncertain characteristics of energy systems. Besides, the model can be used for answering questions related to types, times, demands and mitigations of energy systems planning practices, with the objective of minimizing system cost over a long-time planning horizon. The solutions can help generate electricity-generation schemes and capacity-expansion plans under different GHG-mitigation options and electricity-demand levels. Tradeoffs among system cost, energy security, and emission management can also be tackled. A high system cost will increase renewable energy supply and reduce GHG emission, while a desire for a low cost will run into risks of a high energy deficiency and a high GHG emission.
Robust Optimisation for Hydroelectric System Operation under Uncertainty
Apostolopoulou, D.; De Greve, Z.; McCulloch, M.
2018-01-01
In this paper, we propose an optimal dispatch scheme for a cascade hydroelectric power system that maximises the head levels of each dam, and minimises the spillage effects taking into account uncertainty in the net load variations, i.e., the difference between the load and the renewable resources, and inflows to the cascade. By maximising the head levels of each dam the volume of water stored, which is a metric of system resiliency, is maximised. In this regard, the operation of the cascade ...
Iso-uncertainty control in an experimental fluoroscopy system
International Nuclear Information System (INIS)
Siddique, S.; Fiume, E.; Jaffray, D. A.
2014-01-01
Purpose: X-ray fluoroscopy remains an important imaging modality in a number of image-guided procedures due to its real-time nature and excellent spatial detail. However, the radiation dose delivered raises concerns about its use particularly in lengthy treatment procedures (>0.5 h). The authors have previously presented an algorithm that employs feedback of geometric uncertainty to control dose while maintaining a desired targeting uncertainty during fluoroscopic tracking of fiducials. The method was tested using simulations of motion against controlled noise fields. In this paper, the authors embody the previously reported method in a physical prototype and present changes to the controller required to function in a practical setting. Methods: The metric for feedback used in this study is based on the trace of the covariance of the state of the system, tr(C). The state is defined here as the 2D location of a fiducial on a plane parallel to the detector. A relationship between this metric and the tube current is first developed empirically. This relationship is extended to create a manifold that incorporates a latent variable representing the estimated background attenuation. The manifold is then used within the controller to dynamically adjust the tube current and maintain a specified targeting uncertainty. To evaluate the performance of the proposed method, an acrylic sphere (1.6 mm in diameter) was tracked at tube currents ranging from 0.5 to 0.9 mA (0.033 s) at a fixed energy of 80 kVp. The images were acquired on a Varian Paxscan 4030A (2048 × 1536 pixels, ∼100 cm source-to-axis distance, ∼160 cm source-to-detector distance). The sphere was tracked using a particle filter under two background conditions: (1) uniform sheets of acrylic and (2) an acrylic wedge. The measured tr(C) was used in conjunction with a learned manifold to modulate the tube current in order to maintain a specified uncertainty as the sphere traversed regions of varying thickness
DEFF Research Database (Denmark)
Cheali, Peam; Gernaey, Krist; Sin, Gürkan
2015-01-01
Capital investment, next to the product demand, sales, and production costs, is one of the key metrics commonly used for project evaluation and feasibility assessment. Estimating the investment costs of a new product/process alternative during early-stage design is a challenging task, which......) the Monte Carlo technique as an error propagation method based on expert input when cost data are not available. Four well-known models for early-stage cost estimation are reviewed and analyzed using the methodology. The significance of uncertainties of cost data for early-stage process design...
Switching Fuzzy Guaranteed Cost Control for Nonlinear Networked Control Systems
Directory of Open Access Journals (Sweden)
Linqin Cai
2014-01-01
Full Text Available This paper deals with the problem of guaranteed cost control for a class of nonlinear networked control systems (NCSs with time-varying delay. A guaranteed cost controller design method is proposed to achieve the desired control performance based on the switched T-S fuzzy model. The switching mechanism is introduced to handle the uncertainties of NCSs. Based on Lyapunov functional approach, some sufficient conditions for the existence of state feedback robust guaranteed cost controller are presented. Simulation results show that the proposed method is effective to guarantee system’s global asymptotic stability and quality of service (QoS.
Hadjimichael, A.; Corominas, L.; Comas, J.
2017-12-01
With sustainable development as their overarching goal, urban wastewater system (UWS) managers need to take into account multiple social, economic, technical and environmental facets related to their decisions. In this complex decision-making environment, uncertainty can be formidable. It is present both in the ways the system is interpreted stochastically, but also in its natural ever-shifting behavior. This inherent uncertainty suggests that wiser decisions would be made under an adaptive and iterative decision-making regime. No decision-support framework has been presented in the literature to effectively addresses all these needs. The objective of this work is to describe such a conceptual framework to evaluate and compare alternative solutions for various UWS challenges within an adaptive management structure. Socio-economic aspects such as externalities are taken into account, along with other traditional criteria as necessary. Robustness, reliability and resilience analyses test the performance of the system against present and future variability. A valuation uncertainty analysis incorporates uncertain valuation assumptions in the decision-making process. The framework is demonstrated with an application to a case study presenting a typical problem often faced by managers: poor river water quality, increasing population, and more stringent water quality legislation. The application of the framework made use of: i) a cost-benefit analysis including monetized environmental benefits and damages; ii) a robustness analysis of system performance against future conditions; iii) reliability and resilience analyses of the system given contextual variability; and iv) a valuation uncertainty analysis of model parameters. The results suggest that the installation of bigger volumes would give rise to increased benefits despite larger capital costs, as well as increased robustness and resilience. Population numbers appear to affect the estimated benefits most, followed by
Analysis of Uncertainty in a Middle-Cost Device for 3D Measurements in BIM Perspective
Directory of Open Access Journals (Sweden)
Alonso Sánchez
2016-09-01
Full Text Available Medium-cost devices equipped with sensors are being developed to get 3D measurements. Some allow for generating geometric models and point clouds. Nevertheless, the accuracy of these measurements should be evaluated, taking into account the requirements of the Building Information Model (BIM. This paper analyzes the uncertainty in outdoor/indoor three-dimensional coordinate measures and point clouds (using Spherical Accuracy Standard (SAS methods for Eyes Map, a medium-cost tablet manufactured by e-Capture Research & Development Company, Mérida, Spain. To achieve it, in outdoor tests, by means of this device, the coordinates of targets were measured from 1 to 6 m and cloud points were obtained. Subsequently, these were compared to the coordinates of the same targets measured by a Total Station. The Euclidean average distance error was 0.005–0.027 m for measurements by Photogrammetry and 0.013–0.021 m for the point clouds. All of them satisfy the tolerance for point cloud acquisition (0.051 m according to the BIM Guide for 3D Imaging (General Services Administration; similar results are obtained in the indoor tests, with values of 0.022 m. In this paper, we establish the optimal distances for the observations in both, Photogrammetry and 3D Photomodeling modes (outdoor and point out some working conditions to avoid in indoor environments. Finally, the authors discuss some recommendations for improving the performance and working methods of the device.
Directory of Open Access Journals (Sweden)
Shaopeng Zhong
2013-01-01
Full Text Available Focusing on the first-best marginal cost pricing (MCP in a stochastic network with both travel demand uncertainty and stochastic perception errors within the travelers’ route choice decision processes, this paper develops a perceived risk-based stochastic network marginal cost pricing (PRSN-MCP model. Numerical examples based on an integrated method combining the moment analysis approach, the fitting distribution method, and the reliability measures are also provided to demonstrate the importance and properties of the proposed model. The main finding is that ignoring the effect of travel time reliability and travelers’ perception errors may significantly reduce the performance of the first-best MCP tolls, especially under high travelers’ confidence and network congestion levels. The analysis result could also enhance our understanding of (1 the effect of stochastic perception error (SPE on the perceived travel time distribution and the components of road toll; (2 the effect of road toll on the actual travel time distribution and its reliability measures; (3 the effect of road toll on the total network travel time distribution and its statistics; and (4 the effect of travel demand level and the value of reliability (VoR level on the components of road toll.
Least-cost failure diagnosis in uncertain reliability systems
International Nuclear Information System (INIS)
Cox, Louis Anthony; Chiu, Steve Y.; Sun Xiaorong
1996-01-01
In many textbook solutions, for systems failure diagnosis problems studied using reliability theory and artificial intelligence, the prior probabilities of different failure states can be estimated and used to guide the sequential search for failed components after the whole system fails. In practice, however, both the component failure probabilities and the structure function of the system being examined--i.e., the mapping between the states of its components and the state of the system--may not be known with certainty. At best:, the probabilities of different hypothesized system descriptions, each specifying the component failure probabilities and the system's structure function, may be known to a useful approximation, perhaps based on sample data and previous experience. Cost-effective diagnosis of the system's failure state is then a challenging problem. Although the probabilities of component failures are aleatory, uncertainties about these probabilities and about the system structure function are epistemic. This paper examines how to make best use of both epistemic prior probabilities for system descriptions and the information gleaned from costly inspections of component states after the system fails, to minimize the average cost of identifying the failure state. Two approaches are introduced for systems dominated by aleatory uncertainties, one motivated by information theory and the other based on the idea of trying to prove a hypothesis about the identity of the failure state as efficiently as possible. While the general problem of cost-effective failure diagnosis is computationally intractable (NP-hard), both heuristics provide useful approximations on small to moderate sized problems and optimal results for certain common types of reliability systems, including series, parallel, parallel-series, and k-out-of-n systems. A hybrid heuristic that adaptively chooses which heuristic to apply next after any sequence of observations (component test results
Sensing risk, fearing uncertainty: Systems science approach to change.
Directory of Open Access Journals (Sweden)
Ivo P Janecka
2014-03-01
Full Text Available BackgroundMedicine devotes its primary focus to understanding change, from cells to network relationships; observations of non-linearity are inescapable. Recent events provide extraordinary examples of major non-linear surprises within the societal system: human genome-from anticipated 100,000+ genes to only 20,000+; junk DNA-initially ignored but now proven to control genetic processes; economic reversals-bursting of bubbles in technology, housing, finance; foreign wars; relentless rise in obesity, neurodegenerative diseases.There are two attributes of systems science that are especially relevant to this research: One- it offers a method for creating a structural context with a guiding path to pragmatic knowledge; and, two- it gives pre-eminence to sensory input capable to register, evaluate, and react to change. Material / MethodPublic domain records of change, during the last fifty years, have been studied in the context of systems science, the dynamic systems model, and various cycles. Results / Conclusions Change is dynamic, ever-present, never isolated, and of variable impact; it reflects innumerable relationships among contextual systems; change can be perceived as risk or uncertainty depending upon how the assessment is made; risk is quantifiable by sensory input and generates a degree of rational optimism; uncertainty is not quantifiable and evokes fear; trust is key to sharing risk; the measurable financial credit can be a proxy for societal trust; expanding credit dilutes trust; when a credit bubble bursts, so will trust; absence of trust paralyzes systems’ relationships leading to disorganized complexity which prevents value creation and heightens the probability of random events; disappearance of value, accompanied by chaos, threatens all systems.From personal health to economic sustainability and collective rationality, most examined components of the societal system were found not to be optimized and trust was not in evidence.
Yao, Wen; Chen, Xiaoqian; Huang, Yiyong; van Tooren, Michel
2013-06-01
To assess the on-orbit servicing (OOS) paradigm and optimize its utilities by taking advantage of its inherent flexibility and responsiveness, the OOS system assessment and optimization methods based on lifecycle simulation under uncertainties are studied. The uncertainty sources considered in this paper include both the aleatory (random launch/OOS operation failure and on-orbit component failure) and the epistemic (the unknown trend of the end-used market price) types. Firstly, the lifecycle simulation under uncertainties is discussed. The chronological flowchart is presented. The cost and benefit models are established, and the uncertainties thereof are modeled. The dynamic programming method to make optimal decision in face of the uncertain events is introduced. Secondly, the method to analyze the propagation effects of the uncertainties on the OOS utilities is studied. With combined probability and evidence theory, a Monte Carlo lifecycle Simulation based Unified Uncertainty Analysis (MCS-UUA) approach is proposed, based on which the OOS utility assessment tool under mixed uncertainties is developed. Thirdly, to further optimize the OOS system under mixed uncertainties, the reliability-based optimization (RBO) method is studied. To alleviate the computational burden of the traditional RBO method which involves nested optimum search and uncertainty analysis, the framework of Sequential Optimization and Mixed Uncertainty Analysis (SOMUA) is employed to integrate MCS-UUA, and the RBO algorithm SOMUA-MCS is developed. Fourthly, a case study on the OOS system for a hypothetical GEO commercial communication satellite is investigated with the proposed assessment tool. Furthermore, the OOS system is optimized with SOMUA-MCS. Lastly, some conclusions are given and future research prospects are highlighted.
Uncertainty and sensitivity analysis using probabilistic system assessment code. 1
International Nuclear Information System (INIS)
Honma, Toshimitsu; Sasahara, Takashi.
1993-10-01
This report presents the results obtained when applying the probabilistic system assessment code under development to the PSACOIN Level 0 intercomparison exercise organized by the Probabilistic System Assessment Code User Group in the Nuclear Energy Agency (NEA) of OECD. This exercise is one of a series designed to compare and verify probabilistic codes in the performance assessment of geological radioactive waste disposal facilities. The computations were performed using the Monte Carlo sampling code PREP and post-processor code USAMO. The submodels in the waste disposal system were described and coded with the specification of the exercise. Besides the results required for the exercise, further additional uncertainty and sensitivity analyses were performed and the details of these are also included. (author)
Stochastic dynamic analysis of marine risers considering Gaussian system uncertainties
Ni, Pinghe; Li, Jun; Hao, Hong; Xia, Yong
2018-03-01
This paper performs the stochastic dynamic response analysis of marine risers with material uncertainties, i.e. in the mass density and elastic modulus, by using Stochastic Finite Element Method (SFEM) and model reduction technique. These uncertainties are assumed having Gaussian distributions. The random mass density and elastic modulus are represented by using the Karhunen-Loève (KL) expansion. The Polynomial Chaos (PC) expansion is adopted to represent the vibration response because the covariance of the output is unknown. Model reduction based on the Iterated Improved Reduced System (IIRS) technique is applied to eliminate the PC coefficients of the slave degrees of freedom to reduce the dimension of the stochastic system. Monte Carlo Simulation (MCS) is conducted to obtain the reference response statistics. Two numerical examples are studied in this paper. The response statistics from the proposed approach are compared with those from MCS. It is noted that the computational time is significantly reduced while the accuracy is kept. The results demonstrate the efficiency of the proposed approach for stochastic dynamic response analysis of marine risers.
Roefs, Ivar; Meulman, Brendo; Vreeburg, Jan H G; Spiller, Marc
2017-02-01
Sanitation systems are built to be robust, that is, they are dimensioned to cope with population growth and other variability that occurs throughout their lifetime. It was recently shown that building sanitation systems in phases is more cost effective than one robust design. This phasing can take place by building small autonomous decentralised units that operate closer to the actual demand. Research has shown that variability and uncertainty in urban development does affect the cost effectiveness of this approach. Previous studies do not, however, consider the entire sanitation system from collection to treatment. The aim of this study is to assess the economic performance of three sanitation systems with different scales and systems characteristics under a variety of urban development pathways. Three systems are studied: (I) a centralised conventional activated sludge treatment, (II) a community on site source separation grey water and black water treatment and (III) a hybrid with grey water treatment at neighbourhood scale and black water treatment off site. A modelling approach is taken that combines a simulation of greenfield urban growth, a model of the wastewater collection and treatment infrastructure design properties and a model that translates design parameters into discounted asset lifetime costs. Monte Carlo simulations are used to evaluate the economic performance under uncertain development trends. Results show that the conventional system outperforms both of the other systems when total discounted lifetime costs are assessed, because it benefits from economies of scale. However, when population growth is lower than expected, the source-separated system is more cost effective, because of reduced idle capacity. The hybrid system is not competitive under any circumstance due to the costly double piping and treatment. Copyright © 2016 Elsevier Ltd. All rights reserved.
Robust uncertainty evaluation for system identification on distributed wireless platforms
Crinière, Antoine; Döhler, Michael; Le Cam, Vincent; Mevel, Laurent
2016-04-01
Health monitoring of civil structures by system identification procedures from automatic control is now accepted as a valid approach. These methods provide frequencies and modeshapes from the structure over time. For a continuous monitoring the excitation of a structure is usually ambient, thus unknown and assumed to be noise. Hence, all estimates from the vibration measurements are realizations of random variables with inherent uncertainty due to (unknown) process and measurement noise and finite data length. The underlying algorithms are usually running under Matlab under the assumption of large memory pool and considerable computational power. Even under these premises, computational and memory usage are heavy and not realistic for being embedded in on-site sensor platforms such as the PEGASE platform. Moreover, the current push for distributed wireless systems calls for algorithmic adaptation for lowering data exchanges and maximizing local processing. Finally, the recent breakthrough in system identification allows us to process both frequency information and its related uncertainty together from one and only one data sequence, at the expense of computational and memory explosion that require even more careful attention than before. The current approach will focus on presenting a system identification procedure called multi-setup subspace identification that allows to process both frequencies and their related variances from a set of interconnected wireless systems with all computation running locally within the limited memory pool of each system before being merged on a host supervisor. Careful attention will be given to data exchanges and I/O satisfying OGC standards, as well as minimizing memory footprints and maximizing computational efficiency. Those systems are built in a way of autonomous operations on field and could be later included in a wide distributed architecture such as the Cloud2SM project. The usefulness of these strategies is illustrated on
International Nuclear Information System (INIS)
Rout, Ullash K.; Blesl, Markus; Fahl, Ulrich; Remme, Uwe; Voss, Alfred
2009-01-01
The diffusion of promising energy technologies in the market depends on their future energy production-cost development. When analyzing these technologies in an integrated assessment model using endogenous technological learning, the uncertainty in the assumed learning rates (LRs) plays a crucial role in the production-cost development and model outcomes. This study examines the uncertainty in LRs of some energy technologies under endogenous global learning implementation and presents a floor-cost modeling procedure to systematically regulate the uncertainty in LRs of energy technologies. The article narrates the difficulties of data assimilation, as compatible with mixed integer programming segmentations, and comprehensively presents the causes of uncertainty in LRs. This work is executed using a multi-regional and long-horizon energy system model based on 'TIMES' framework. All regions receive an economic advantage to learn in a common domain, and resource-ample regions obtain a marginal advantage for better exploitation of the learning technologies, due to a lower supply-side fuel-cost development. The lowest learning investment associated with the maximum LR mobilizes more deployment of the learning technologies. The uncertainty in LRs has an impact on the diffusion of energy technologies tested, and therefore this study scrutinizes the role of policy support for some of the technologies investigated. (author)
Maintenance cost models in deregulated power systems under opportunity costs
International Nuclear Information System (INIS)
Al-Arfaj, K.; Dahal, K.; Azaiez, M.N.
2007-01-01
In a centralized power system, the operator is responsible for scheduling maintenance. There are different types of maintenance, including corrective maintenance; predictive maintenance; preventive maintenance; and reliability-centred maintenance. The main cause of power failures is poor maintenance. As such, maintenance costs play a significant role in deregulated power systems. They include direct costs associated with material and labor costs as well as indirect costs associated with spare parts inventory, shipment, test equipment, indirect labor, opportunity costs and cost of failure. In maintenance scheduling and planning, the cost function is the only component of the objective function. This paper presented the results of a study in which different components of maintenance costs were modeled. The maintenance models were formulated as an optimization problem with single and multiple objectives and a set of constraints. The maintenance costs models could be used to schedule the maintenance activities of power generators more accurately and to identify the best maintenance strategies over a period of time as they consider failure and opportunity costs in a deregulated environment. 32 refs., 4 tabs., 4 figs
H 2 guaranteed cost control of discrete linear systems
Directory of Open Access Journals (Sweden)
Colmenares W.
2000-01-01
Full Text Available This paper presents necessary and sufficient conditions for the existence of a quadratically stabilizing output feedback controller which also assures H 2 guaranteed cost performance on a discrete linear uncertain system where the uncertainty is of the norm bounded type. The conditions are presented as a collection of linear matrix inequalities.The solution, however requires a search over a scalar parameter space.
Resilient guaranteed cost control of a power system.
Soliman, Hisham M; Soliman, Mostafa H; Hassan, Mohammad F
2014-05-01
With the development of power system interconnection, the low-frequency oscillation is becoming more and more prominent which may cause system separation and loss of energy to consumers. This paper presents an innovative robust control for power systems in which the operating conditions are changing continuously due to load changes. However, practical implementation of robust control can be fragile due to controller inaccuracies (tolerance of resistors used with operational amplifiers). A new design of resilient (non-fragile) robust control is given that takes into consideration both model and controller uncertainties by an iterative solution of a set of linear matrix inequalities (LMI). Both uncertainties are cast into a norm-bounded structure. A sufficient condition is derived to achieve the desired settling time for damping power system oscillations in face of plant and controller uncertainties. Furthermore, an improved controller design, resilient guaranteed cost controller, is derived to achieve oscillations damping in a guaranteed cost manner. The effectiveness of the algorithm is shown for a single machine infinite bus system, and then, it is extended to multi-area power system.
Entropy Evolution and Uncertainty Estimation with Dynamical Systems
Directory of Open Access Journals (Sweden)
X. San Liang
2014-06-01
Full Text Available This paper presents a comprehensive introduction and systematic derivation of the evolutionary equations for absolute entropy H and relative entropy D, some of which exist sporadically in the literature in different forms under different subjects, within the framework of dynamical systems. In general, both H and D are dissipated, and the dissipation bears a form reminiscent of the Fisher information; in the absence of stochasticity, dH/dt is connected to the rate of phase space expansion, and D stays invariant, i.e., the separation of two probability density functions is always conserved. These formulas are validated with linear systems, and put to application with the Lorenz system and a large-dimensional stochastic quasi-geostrophic flow problem. In the Lorenz case, H falls at a constant rate with time, implying that H will eventually become negative, a situation beyond the capability of the commonly used computational technique like coarse-graining and bin counting. For the stochastic flow problem, it is first reduced to a computationally tractable low-dimensional system, using a reduced model approach, and then handled through ensemble prediction. Both the Lorenz system and the stochastic flow system are examples of self-organization in the light of uncertainty reduction. The latter particularly shows that, sometimes stochasticity may actually enhance the self-organization process.
Reducing uncertainty in nitrogen budgets for African livestock systems
International Nuclear Information System (INIS)
Rufino, M C; Brandt, P; Herrero, M; Butterbach-Bahl, K
2014-01-01
Livestock is poorly represented in N budgets for the African continent although some studies have examined livestock-related N flows at different levels. Livestock plays an important role in N cycling and therefore on N budgets including livestock-related flows. This study reviews the literature on N budgets for Africa to identify factors contributing to uncertainties. Livestock densities are usually modelled because of the lack of observational spatial data. Even though feed availability and quality varies across seasons, most studies use constant livestock excretion rates, and excreta are usually assumed to be uniformly distributed onto the land. Major uncertainties originate in the fraction of manure managed, and emission factors which may not reflect the situation of Africa. N budgets use coarse assumptions on production, availability, and use of crop residues as livestock feed. No flows between croplands–livestock and rangelands reflect the lack of data. Joint efforts are needed for spatial data collection of livestock data, crowdsourcing appears to be a promising option. The focus of the assessment of N budgets must go beyond croplands to include livestock and crop–livestock flows. We propose a nested systems definition of livestock systems to link local, regional level, and continental level and to increase the usefulness of point measurements of N losses. Scientists working at all levels should generate data to calibrate process-based models. Measurements in the field should not only concentrate on greenhouse gas emissions, but need to include crop and livestock production measurements, soil stock changes and other N loss pathways such as leaching, run-off and volatilization to assess management practices and trade-offs. Compared to the research done in other continents on N flows in livestock systems, there are few data for Africa, and therefore concerted effort will be needed to generate sufficient data for modelling. (paper)
Uncertainty analysis of nonlinear systems employing the first-order reliability method
International Nuclear Information System (INIS)
Choi, Chan Kyu; Yoo, Hong Hee
2012-01-01
In most mechanical systems, properties of the system elements have uncertainties due to several reasons. For example, mass, stiffness coefficient of a spring, damping coefficient of a damper or friction coefficients have uncertain characteristics. The uncertain characteristics of the elements have a direct effect on the system performance uncertainty. It is very important to estimate the performance uncertainty since the performance uncertainty is directly related to manufacturing yield and consumer satisfaction. Due to this reason, the performance uncertainty should be estimated accurately and considered in the system design. In this paper, performance measures are defined for nonlinear vibration systems and the performance measure uncertainties are estimated employing the first order reliability method (FORM). It was found that the FORM could provide good results in spite of the system nonlinear characteristics. Comparing to the results obtained by Monte Carlo Simulation (MCS), the accuracy of the uncertainty analysis results obtained by the FORM is validated
Quantum uncertainty in critical systems with three spins interaction
International Nuclear Information System (INIS)
Carrijo, Thiago M; Avelar, Ardiley T; Céleri, Lucas C
2015-01-01
In this article we consider two spin-1/2 chains described, respectively, by the thermodynamic limit of the XY model with the usual two site interaction, and an extension of this model (without taking the thermodynamics limit), called XYT, were a three site interaction term is presented. To investigate the critical behaviour of such systems we employ tools from quantum information theory. Specifically, we show that the local quantum uncertainty, a quantity introduced in order to quantify the minimum quantum share of the variance of a local measurement, can be used to indicate quantum phase transitions presented by these models at zero temperature. Due to the connection of this quantity with the quantum Fisher information, the results presented here may be relevant for quantum metrology and quantum thermodynamics. (paper)
System convergence in transport models: algorithms efficiency and output uncertainty
DEFF Research Database (Denmark)
Rich, Jeppe; Nielsen, Otto Anker
2015-01-01
of this paper is to analyse convergence performance for the external loop and to illustrate how an improper linkage between the converging parts can lead to substantial uncertainty in the final output. Although this loop is crucial for the performance of large-scale transport models it has not been analysed...... much in the literature. The paper first investigates several variants of the Method of Successive Averages (MSA) by simulation experiments on a toy-network. It is found that the simulation experiments produce support for a weighted MSA approach. The weighted MSA approach is then analysed on large......-scale in the Danish National Transport Model (DNTM). It is revealed that system convergence requires that either demand or supply is without random noise but not both. In that case, if MSA is applied to the model output with random noise, it will converge effectively as the random effects are gradually dampened...
Automated system for calculating the uncertainty of standards
International Nuclear Information System (INIS)
Harvel, C.D.
1990-01-01
Working Calibration and Test Material (WCTM) solutions are essential as standards in the surveillance of analytical methods, the calibration of equipment and methods, and the training and testing of laboratory personnel. Before the WCTM can be used it must be characterized. That is, the WCTM concentration and its associated uncertainty must be estimated. The characterization of a WCTM is a tedious process. The chemistry and subsequent statistical analysis require a significant amount of care. For a nonstatistician, the statistical analysis of a WCTM characterization can be quite difficult. In addition, the WCTM traceability and characterization must be thoroughly documented as required by DOE Order 5633.3 [1]. An automated system can easily do the statistical analysis and provide the necessary documentation. 3 refs., 2 figs
Epistemic uncertainty propagation in energy flows between structural vibrating systems
Xu, Menghui; Du, Xiaoping; Qiu, Zhiping; Wang, Chong
2016-03-01
A dimension-wise method for predicting fuzzy energy flows between structural vibrating systems coupled by joints with epistemic uncertainties is established. Based on its Legendre polynomial approximation at α=0, both the minimum and maximum point vectors of the energy flow of interest are calculated dimension by dimension within the space spanned by the interval parameters determined by fuzzy those at α=0 and the resulted interval bounds are used to assemble the concerned fuzzy energy flows. Besides the proposed method, vertex method as well as two current methods is also applied. Comparisons among results by different methods are accomplished by two numerical examples and the accuracy of all methods is simultaneously verified by Monte Carlo simulation.
Directory of Open Access Journals (Sweden)
Julian Alexander Melo Rodriguez
2016-09-01
Full Text Available Objectives: This paper presents a new methodology for analyzing the vulnerability of power systems including uncertainty in some variables. Method: The methodology optimizes a Bi-level mixed integer model. Costs associated with power generation and load shedding are minimized at the lowest level whereas at the higher level the damage in the power system, represented by the load shedding, is maximized. Fuzzy logic type 2 is used to model the uncertainty in both linguistic variables and numeric variables. The linguistic variables model the factors of the geographical environment while numeric variables model parameters of the power system. Results: The methodology was validated by using a modified IEEE RTS-96 test system. The results show that by including particularities of the geographical environment different vulnerabilities are detected in the power system. Moreover, it was possible to identify that the most critical component is the line 112-123 because it had 16 attacks in 18 scenarios, and that the maximum load shedding of the system varies from 145 to 1258 MW. Conclusions: This methodology can be used to coordinate and refine protection plans of the power system infrastructure. Funding: EMC-UN research group.
Implementation of a Cost-Accounting System for Visibility of Weapon Systems Life-Cycle Costs
National Research Council Canada - National Science Library
Ugone, Mary
2001-01-01
... costs through activity-based costing and management. The system must deliver timely, integrated data for management purposes to permit understanding of total weapon costs, provide a basis for estimating costs of future systems, and feed other tools for life-cycle cost management.
Fazzari, D M
2001-01-01
This report presents the results of an evaluation of the Total Measurement Uncertainty (TMU) for the Canberra manufactured Segmented Gamma Scanner Assay System (SGSAS) as employed at the Hanford Plutonium Finishing Plant (PFP). In this document, TMU embodies the combined uncertainties due to all of the individual random and systematic sources of measurement uncertainty. It includes uncertainties arising from corrections and factors applied to the analysis of transuranic waste to compensate for inhomogeneities and interferences from the waste matrix and radioactive components. These include uncertainty components for any assumptions contained in the calibration of the system or computation of the data. Uncertainties are propagated at 1 sigma. The final total measurement uncertainty value is reported at the 95% confidence level. The SGSAS is a gamma assay system that is used to assay plutonium and uranium waste. The SGSAS system can be used in a stand-alone mode to perform the NDA characterization of a containe...
Energy Technology Data Exchange (ETDEWEB)
Jovanovich, A.P.; Stone, M.L.; Taylor, G.C.
1979-07-01
The uncertainties in Volume I without extensive additional engineering effort were identified and quantified. Substantial uncertainty was found in several critical variables, allowing a broad range of possible values. Calculations of the cost impact associated with such broad ranges, however, did not always result in significant differences. Seven major areas of pollution control activity were judged to warrant the assessment effort. Three of these areas were found to contain significant uncertainty and additional research is suggested. These areas are: H/sub 2/S removal from the retort gas stream (Stretford process); organic removal from process wastewaters (bio-oxidation or other alternatives); and slurry backfilling of spent Modified In Situ (MIS) retorts. The overall results of the assessment and analysis process are summarized in Table 1-1 in terms of total cost for pollution control. The distributions have been divided into three ranges in this table. A center range is given which contains 80% to 90% probability, and the costs outside this range with probabilities are given. The full distributions can be found in Section 5.0. The subjective probability distributions are a quantification of opinion. The probability of encountering costs below the low figure or above the high figure for each process and scenario is judged to be nearly zero.
Cost Accounting System for fusion studies
International Nuclear Information System (INIS)
Hamilton, W.R.; Keeton, D.C.; Thomson, S.L.
1985-12-01
A Cost Accounting System that is applicable to all magnetic fusion reactor design studies has been developed. This system provides: (1) definitions of the elements of cost and methods for the combination of these elements to form a cost estimate; (2) a Code of Accounts that uses a functional arrangement for identification of the plant components; and (3) definitions and methods to analyze actual cost data so that the data can be directly reported into this Cost Accounting System. The purpose of the Cost Accounting System is to provide the structure for the development of a fusion cost data base and for the development of validated cost estimating procedures. This system has been developed through use at the Fusion Engineering Design Center (FEDC) and has been applied to different confinement concepts (tokamaks and tandem mirrors) and to different types of projects (experimental devices and commercial power plants). The use of this Cost Accounting System by all magnetic fusion projects will promote the development of a common cost data base, allow the direct comparison of cost estimates, and ultimately establish the cost credibility of the program
Cost Accounting System for fusion studies
Energy Technology Data Exchange (ETDEWEB)
Hamilton, W.R.; Keeton, D.C.; Thomson, S.L.
1985-12-01
A Cost Accounting System that is applicable to all magnetic fusion reactor design studies has been developed. This system provides: (1) definitions of the elements of cost and methods for the combination of these elements to form a cost estimate; (2) a Code of Accounts that uses a functional arrangement for identification of the plant components; and (3) definitions and methods to analyze actual cost data so that the data can be directly reported into this Cost Accounting System. The purpose of the Cost Accounting System is to provide the structure for the development of a fusion cost data base and for the development of validated cost estimating procedures. This system has been developed through use at the Fusion Engineering Design Center (FEDC) and has been applied to different confinement concepts (tokamaks and tandem mirrors) and to different types of projects (experimental devices and commercial power plants). The use of this Cost Accounting System by all magnetic fusion projects will promote the development of a common cost data base, allow the direct comparison of cost estimates, and ultimately establish the cost credibility of the program.
Practical reliability and uncertainty quantification in complex systems : final report.
Energy Technology Data Exchange (ETDEWEB)
Grace, Matthew D.; Ringland, James T.; Marzouk, Youssef M. (Massachusetts Institute of Technology, Cambridge, MA); Boggs, Paul T.; Zurn, Rena M.; Diegert, Kathleen V. (Sandia National Laboratories, Albuquerque, NM); Pebay, Philippe Pierre; Red-Horse, John Robert (Sandia National Laboratories, Albuquerque, NM)
2009-09-01
The purpose of this project was to investigate the use of Bayesian methods for the estimation of the reliability of complex systems. The goals were to find methods for dealing with continuous data, rather than simple pass/fail data; to avoid assumptions of specific probability distributions, especially Gaussian, or normal, distributions; to compute not only an estimate of the reliability of the system, but also a measure of the confidence in that estimate; to develop procedures to address time-dependent or aging aspects in such systems, and to use these models and results to derive optimal testing strategies. The system is assumed to be a system of systems, i.e., a system with discrete components that are themselves systems. Furthermore, the system is 'engineered' in the sense that each node is designed to do something and that we have a mathematical description of that process. In the time-dependent case, the assumption is that we have a general, nonlinear, time-dependent function describing the process. The major results of the project are described in this report. In summary, we developed a sophisticated mathematical framework based on modern probability theory and Bayesian analysis. This framework encompasses all aspects of epistemic uncertainty and easily incorporates steady-state and time-dependent systems. Based on Markov chain, Monte Carlo methods, we devised a computational strategy for general probability density estimation in the steady-state case. This enabled us to compute a distribution of the reliability from which many questions, including confidence, could be addressed. We then extended this to the time domain and implemented procedures to estimate the reliability over time, including the use of the method to predict the reliability at a future time. Finally, we used certain aspects of Bayesian decision analysis to create a novel method for determining an optimal testing strategy, e.g., we can estimate the 'best' location to
Uncertainty-accounting environmental policy and management of water systems.
Baresel, Christian; Destouni, Georgia
2007-05-15
Environmental policies for water quality and ecosystem management do not commonly require explicit stochastic accounts of uncertainty and risk associated with the quantification and prediction of waterborne pollutant loads and abatement effects. In this study, we formulate and investigate a possible environmental policy that does require an explicit stochastic uncertainty account. We compare both the environmental and economic resource allocation performance of such an uncertainty-accounting environmental policy with that of deterministic, risk-prone and risk-averse environmental policies under a range of different hypothetical, yet still possible, scenarios. The comparison indicates that a stochastic uncertainty-accounting policy may perform better than deterministic policies over a range of different scenarios. Even in the absence of reliable site-specific data, reported literature values appear to be useful for such a stochastic account of uncertainty.
Intelligent systems in oil field development under uncertainty
Energy Technology Data Exchange (ETDEWEB)
Pacheco, Marco A.C.; Vellasco, Marley M.B.R. (eds.) [PUC-Rio, Rio de Janeiro (Brazil). Dept. of Electrical Engineering
2009-07-01
Intelligent Systems use a range of methodologies for analysis, pre-processing, storage, organization, enhancing and mining of operational data, turning it into useful information and knowledge for decision makers in business enterprises. These intelligent technologies for decision support have been used with success by companies and organizations that are looking for competitive advantages whenever the issues on forecast, optimization, risks analysis, fraud detection, and decision under uncertainties are presented. Intelligent Systems (IS) offer to managers and decision makers the best solutions for complex applications, normally considered difficult, very restrictive or even impossible. The use of such techniques leads to a revolutionary process which has a significant impact in the business management strategy, by providing on time, correct information, ready to use. Computational intelligence techniques, especially genetic algorithms, genetic programming, neural networks, fuzzy logic and neuro-fuzzy as well as modern finance theories, such as real options theory, are here presented and exemplified in oil and gas exploitation and production. This book is addressed to executives and students, directly involved or interested in intelligent management in different fields. (orig.)
Moreno, Rodrigo; Street, Alexandre; Arroyo, José M; Mancarella, Pierluigi
2017-08-13
Electricity grid operators and planners need to deal with both the rapidly increasing integration of renewables and an unprecedented level of uncertainty that originates from unknown generation outputs, changing commercial and regulatory frameworks aimed to foster low-carbon technologies, the evolving availability of market information on feasibility and costs of various technologies, etc. In this context, there is a significant risk of locking-in to inefficient investment planning solutions determined by current deterministic engineering practices that neither capture uncertainty nor represent the actual operation of the planned infrastructure under high penetration of renewables. We therefore present an alternative optimization framework to plan electricity grids that deals with uncertain scenarios and represents increased operational details. The presented framework is able to model the effects of an array of flexible, smart grid technologies that can efficiently displace the need for conventional solutions. We then argue, and demonstrate via the proposed framework and an illustrative example, that proper modelling of uncertainty and operational constraints in planning is key to valuing operationally flexible solutions leading to optimal investment in a smart grid context. Finally, we review the most used practices in power system planning under uncertainty, highlight the challenges of incorporating operational aspects and advocate the need for new and computationally effective optimization tools to properly value the benefits of flexible, smart grid solutions in planning. Such tools are essential to accelerate the development of a low-carbon energy system and investment in the most appropriate portfolio of renewable energy sources and complementary enabling smart technologies.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'. © 2017 The Author(s).
Andrew B. Abel; Janice C. Eberly
1993-01-01
This paper derives closed-form solutions for the investment and market value, under uncertainty, of competitive firms with constant returns to scale production and convex costs of adjustment. Solutions are derived for the case of irreversible investment as well as for reversible investment. Optimal investment is a non-decreasing function of q, the shadow value of capital. The conditions of optimality imply that q cannot contain a bubble; thus, optimal investment depends only on fundamentals. ...
Alquist, Jessica L; Baumeister, Roy F; McGregor, Ian; Core, Tammy J; Benjamin, Ilil; Tice, Dianne M
2018-01-01
People have the ability to make important choices in their lives, but deliberating about these choices can have costs. The present study was designed to test the hypothesis that writing about conflicted personal goals and values (conflict condition) would impair self-control on an unrelated subsequent task as compared to writing about clear personal goals and values (clarity condition). Personal conflict activates the behavioral inhibition system (BIS; Hirsh, Mar, & Peterson, 2012), which may make it harder for participants to successfully execute self-control. In this large ( N =337), pre-registered study participants in the conflict condition performed worse on anagrams than participants in the clarity condition, and the effect of condition on anagram performance was mediated by a subjective uncertainty measure of BIS activation. This suggests that BIS activation leads to poor self-control. Moreover, given that conflict is inherent in the exercise of self-control, results point to BIS activation as a mechanism for why initial acts of self-control impair self-control on subsequent, unrelated tasks.
FORMATION OF THE ENTERPRISE COSTS MANAGEMENT SYSTEM
Directory of Open Access Journals (Sweden)
Borysiuk Iryna
2018-01-01
Full Text Available Introduction. The paper deals with the actual issues of formation of the enterprise management system costs, because in the conditions of an unstable market environment the financial performance depends on the efficiency of the cost management system, competitiveness, financial sustainability and investment attractiveness of any subject of economic activity. Purpose of the article is consolidation of approaches to cost management, theoretical substantiation and development of recommendations regarding the formation of the enterprise cost management system. Results. Development of an enterprise cost management system based on research on the essence and cost management approaches. The goals, tasks, principles, methods, tools, functions and main elements of the cost management system were determined, factors of the external and internal environment of the enterprise, that affect the system of its costs management. Conclusions. Formation of integrated cost management system ensures the successful company operation on the market, production of competitive products based on costs and prices optimization and making a profit, increase of the reasonableness of making managerial decisions.
Role of nuclear fusion in future energy systems and the environment under future uncertainties
International Nuclear Information System (INIS)
Tokimatsu, Koji; Fujino, Jun'ichi; Konishi, Satoshi; Ogawa, Yuichi; Yamaji, Kenji
2003-01-01
Debates about whether or not to invest heavily in nuclear fusion as a future innovative energy option have been made within the context of energy technology development strategies. This is because the prospects for nuclear fusion are quite uncertain and the investments therefore carry the risk of quite large regrets, even though investment is needed in order to develop the technology. The timeframe by which nuclear fusion could become competitive in the energy market has not been adequately studied, nor has roles of the nuclear fusion in energy systems and the environment. The present study has two objectives. One is to reveal the conditions under which nuclear fusion could be introduced economically (hereafter, we refer to such introductory conditions as breakeven prices) in future energy systems. The other objective is to evaluate the future roles of nuclear fusion in energy systems and in the environment. Here we identify three roles that nuclear fusion will take on when breakeven prices are achieved: (i) a portion of the electricity market in 2100, (ii) reduction of annual global total energy systems cost, and (iii) mitigation of carbon tax (shadow price of carbon) under CO 2 constraints. Future uncertainties are key issues in evaluating nuclear fusion. Here we treated the following uncertainties: energy demand scenarios, introduction timeframe for nuclear fusion, capacity projections of nuclear fusion, CO 2 target in 2100, capacity utilization ratio of options in energy/environment technologies, and utility discount rates. From our investigations, we conclude that the presently designed nuclear fusion reactors may be ready for economical introduction into energy systems beginning around 2050-2060, and we can confirm that the favorable introduction of the reactors would reduce both the annual energy systems cost and the carbon tax (the shadow price of carbon) under a CO 2 concentration constraint
Evaluation of Spatial Uncertainties In Modeling of Cadastral Systems
Fathi, Morteza; Teymurian, Farideh
2013-04-01
Cadastre plays an essential role in sustainable development especially in developing countries like Iran. A well-developed Cadastre results in transparency of estates tax system, transparency of data of estate, reduction of action before the courts and effective management of estates and natural sources and environment. Multipurpose Cadastre through gathering of other related data has a vital role in civil, economic and social programs and projects. Iran is being performed Cadastre for many years but success in this program is subject to correct geometric and descriptive data of estates. Since there are various sources of data with different accuracy and precision in Iran, some difficulties and uncertainties are existed in modeling of geometric part of Cadastre such as inconsistency between data in deeds and Cadastral map which cause some troubles in execution of cadastre and result in losing national and natural source, rights of nation. Now there is no uniform and effective technical method for resolving such conflicts. This article describes various aspects of such conflicts in geometric part of cadastre and suggests a solution through some modeling tools of GIS.
Accounting for Epistemic and Aleatory Uncertainty in Early System Design, Phase II
National Aeronautics and Space Administration — This project extends Probability Bounds Analysis to model epistemic and aleatory uncertainty during early design of engineered systems in an Integrated Concurrent...
Accounting for Epistemic and Aleatory Uncertainty in Early System Design, Phase I
National Aeronautics and Space Administration — The proposed work extends Probability Bounds Analysis to model epistemic and aleatory uncertainty during early design of engineered systems in an Integrated...
Quantification of Uncertainties in Integrated Spacecraft System Models, Phase I
National Aeronautics and Space Administration — The proposed effort is to investigate a novel uncertainty quantification (UQ) approach based on non-intrusive polynomial chaos (NIPC) for computationally efficient...
Modeling, design, and simulation of systems with uncertainties
Rauh, Andreas
2011-01-01
This three-fold contribution to the field covers both theory and current research in algorithmic approaches to uncertainty handling, real-life applications such as robotics and biomedical engineering, and fresh approaches to reliably implementing software.
Determination of cost effective waste management system receipt rates
International Nuclear Information System (INIS)
McKee, R.W.; Huber, H.D.
1991-01-01
A comprehensive logistics and cost analysis has been carried out to determine if there are potential benefits to the high-level waste management system for receipt rates other than the current 3,000 MTU/yr design-basis receipt rate. The scope of the analysis includes both a Repository-Only System and a Storage-Only or Basic MRS System. To allow for current uncertainties in facility startup scheduling, cases considering repository startup dates of 2010 and 2015 and MRS startup dates of 1998 and three years prior to the repository have been evaluated. Receipt rates ranging from 1,500 to 6,000 MTU/yr have been considered for both the MRS and the repository. Higher receipt rates appear to be economically justified for both the repository and an MRS. For a repository-only system, minimum costs are found at a repository receipt rate of 6,000 MTU/yr. When a storage-only MRS is included in the system, minimum system costs are also achieved at a repository receipt rate of 6,000 MTU/yr. However, the MRS receipt rate for minimum system costs depends on the MRS startup date and ranges from 3,500 to 6,000 MTU/yr. With a 1998 MRS and a 2010 repository, the added cost of providing the MRS is offset by at-reactor storage cost reductions and the total system cost of $10.0 billion is virtually the same as for the repository-only system
Uncertainty Evaluation of Residential Central Air-conditioning Test System
Li, Haoxue
2018-04-01
According to national standards, property tests of air-conditioning are required. However, test results could be influenced by the precision of apparatus or measure errors. Therefore, uncertainty evaluation of property tests should be conducted. In this paper, the uncertainties are calculated on the property tests of Xinfei13.6 kW residential central air-conditioning. The evaluation result shows that the property tests are credible.
Cost and Performance Model for Photovoltaic Systems
Borden, C. S.; Smith, J. H.; Davisson, M. C.; Reiter, L. J.
1986-01-01
Lifetime cost and performance (LCP) model assists in assessment of design options for photovoltaic systems. LCP is simulation of performance, cost, and revenue streams associated with photovoltaic power systems connected to electric-utility grid. LCP provides user with substantial flexibility in specifying technical and economic environment of application.
Is the uncertainty about climate change too large for expected cost-benefit analysis?
Tol, R.S.J.
2003-01-01
Cost-benefit analysis is only applicable if the variances of both costs and benefits are finite. In the case of climate change, the variances of the net present marginal costs and benefits of greenhouse gas emission reduction need to be finite. Finiteness is hard, if not impossible to prove. The
International Nuclear Information System (INIS)
Shay, M.R.
1990-04-01
The System Engineering Cost Analysis (SECA) capability has been developed by the System Integration Branch of the US Department of Energy's Office of Civilian Radioactive Waste Management for use in assessing the cost performance of alternative waste management system configurations. The SECA capability is designed to provide rapid cost estimates of the waste management system for a given operational scenario and to permit aggregate or detailed cost comparisons for alternative waste system configurations. This capability may be used as an integral part of the System Integration Modeling System (SIMS) or, with appropriate input defining a scenario, as a separate cost analysis model
Costing the OMNIUM-G system 7500
Fortgang, H. R.
1980-01-01
A complete OMNIUM-G System 7500 was cost analyzed for annual production quantities ranging from 25 to 10,000 units per year. Parts and components were subjected to in-depth scrutiny to determine optimum manufacturing processes, coupled with make or buy decisions on materials and small parts. When production quantities increase both labor and material costs reduce substantially. A redesign of the system that was analyzed could result in lower costs when annual production runs approach 100,000 units/year. Material and labor costs for producing 25, 100, 25,000 and 100,00 units are given for 17 subassembly units.
International Nuclear Information System (INIS)
Barhen, J.; Bjerke, M.A.; Cacuci, D.G.; Mullins, C.B.; Wagschal, G.G.
1982-01-01
An advanced methodology for performing systematic uncertainty analysis of time-dependent nonlinear systems is presented. This methodology includes a capability for reducing uncertainties in system parameters and responses by using Bayesian inference techniques to consistently combine prior knowledge with additional experimental information. The determination of best estimates for the system parameters, for the responses, and for their respective covariances is treated as a time-dependent constrained minimization problem. Three alternative formalisms for solving this problem are developed. The two ''off-line'' formalisms, with and without ''foresight'' characteristics, require the generation of a complete sensitivity data base prior to performing the uncertainty analysis. The ''online'' formalism, in which uncertainty analysis is performed interactively with the system analysis code, is best suited for treatment of large-scale highly nonlinear time-dependent problems. This methodology is applied to the uncertainty analysis of a transient upflow of a high pressure water heat transfer experiment. For comparison, an uncertainty analysis using sensitivities computed by standard response surface techniques is also performed. The results of the analysis indicate the following. Major reduction of the discrepancies in the calculation/experiment ratios is achieved by using the new methodology. Incorporation of in-bundle measurements in the uncertainty analysis significantly reduces system uncertainties. Accuracy of sensitivities generated by response-surface techniques should be carefully assessed prior to using them as a basis for uncertainty analyses of transient reactor safety problems
The Launch Systems Operations Cost Model
Prince, Frank A.; Hamaker, Joseph W. (Technical Monitor)
2001-01-01
One of NASA's primary missions is to reduce the cost of access to space while simultaneously increasing safety. A key component, and one of the least understood, is the recurring operations and support cost for reusable launch systems. In order to predict these costs, NASA, under the leadership of the Independent Program Assessment Office (IPAO), has commissioned the development of a Launch Systems Operations Cost Model (LSOCM). LSOCM is a tool to predict the operations & support (O&S) cost of new and modified reusable (and partially reusable) launch systems. The requirements are to predict the non-recurring cost for the ground infrastructure and the recurring cost of maintaining that infrastructure, performing vehicle logistics, and performing the O&S actions to return the vehicle to flight. In addition, the model must estimate the time required to cycle the vehicle through all of the ground processing activities. The current version of LSOCM is an amalgamation of existing tools, leveraging our understanding of shuttle operations cost with a means of predicting how the maintenance burden will change as the vehicle becomes more aircraft like. The use of the Conceptual Operations Manpower Estimating Tool/Operations Cost Model (COMET/OCM) provides a solid point of departure based on shuttle and expendable launch vehicle (ELV) experience. The incorporation of the Reliability and Maintainability Analysis Tool (RMAT) as expressed by a set of response surface model equations gives a method for estimating how changing launch system characteristics affects cost and cycle time as compared to today's shuttle system. Plans are being made to improve the model. The development team will be spending the next few months devising a structured methodology that will enable verified and validated algorithms to give accurate cost estimates. To assist in this endeavor the LSOCM team is part of an Agency wide effort to combine resources with other cost and operations professionals to
Cost of photovoltaic energy systems as determined by balance-of-system costs
Rosenblum, L.
1978-01-01
The effect of the balance-of-system (BOS), i.e., the total system less the modules, on photo-voltaic energy system costs is discussed for multikilowatt, flat-plate systems. Present BOS costs are in the range of 10 to 16 dollars per peak watt (1978 dollars). BOS costs represent approximately 50% of total system cost. The possibility of future BOS cost reduction is examined. It is concluded that, given the nature of BOS costs and the lack of comprehensive national effort focussed on cost reduction, it is unlikely that BOS costs will decline greatly in the next several years. This prognosis is contrasted with the expectations of the Department of Energy National Photovoltaic Program goals and pending legislation in the Congress which require a BOS cost reduction of an order of magnitude or more by the mid-1980s.
Maximum respiratory pressure measuring system : calibration and evaluation of uncertainty
Ferreira, J.L.; Pereira, N.C.; Oliveira Júnior, M.; Vasconcelos, F.H.; Parreira, V.F.; Tierra-Criollo, C.J.
2010-01-01
The objective of this paper is to present a methodology for the evaluation of uncertainties in the measurements results obtained during the calibration of a digital manovacuometer prototype (DM) with a load cell sensor pressure device incorporated. Calibration curves were obtained for both pressure
The costs of uncertainty: regulating health and safety in the Canadian uranium industry
International Nuclear Information System (INIS)
Robinson, I.
1982-04-01
Federalism, and particularly federal/provincial jurisdictional relationships, have led to considerable uncertainty in the regulation of occupational health and safety and of environmental protection in the Canadian uranium mining industry. The two principal uranium producing provinces in Canada are Saskatchewan and Ontario. Since 1978, in an attempt to avoid constitutional issues, both these provinces and the federal government as well have proceeded unilaterally with health and safety reforms for the industry. In Saskatchewan this has resulted in areas of overlapping jurisdiction, which have led to uncertainty over the legal enforceability of the provincial regulations. In Ontario, the province has left significant gaps in the protection of both workers and the environment. Little progress can be expected in eliminating these gaps and overlaps until the current administrative and jurisdictional arrangements are understood
Reliability and Cost Impacts for Attritable Systems
2017-03-23
on reliability and cost: a probabilistic model. Electric Power Systems Research, 72(3), 213-224. Kalbfleisch, J.D. & Prentice, R.L. (1980). The...copyright protection in the United States. AFIT-ENV-MS-17-M-172 RELIABILITY AND COST IMPACTS FOR ATTRITABLE SYSTEMS THESIS Presented to... power of discrete time Markov chains, whether homogeneous or non-homogeneous, to model the reliability and dependability of repairable systems should
International Nuclear Information System (INIS)
McHenry, Mark P.
2013-01-01
The fundamental role of policymakers when considering Advanced Metering Infrastructure (AMI), or ‘smart meters for energy and water infrastructure is to investigate a broad range of complex interrelated issues. These include alternative technical and non-technical options and deployment needs, the cost and benefits of the infrastructure (risks and mitigation measures), and the impact of a number of stakeholders: consumers, distributors, retailers, competitive market operators, competing technology companies, etc. The scale and number of potential variables in the AMI space is an almost unprecedented challenge to policymakers, with the anticipation of new ancillary products and services, associated market contestability, related regulatory and policy amendments, and the adequacy of consumer protection, education, and safety considerations requiring utmost due-diligence. Embarking on AMI investment entails significant technical, implementation, and strategic risk for governments and administering bodies, and an active effort is required to ensure AMI governance and planning maximises the potential benefits, and minimise uncertainties, costs, and risks to stakeholders. This work seeks to clarify AMI fundamentals and discusses the technical and related governance considerations from a dispassionate perspective, yet acknowledges many stakeholders tend to dichotomise debate, and obfuscate both advantages and benefits, and the converse. - Highlights: • AMI presents an almost unprecedented technical and governance policy challenge. • AMI enables vertical integration of electricity, gas, water, IT, and telco entities • AMI investments involve major technical, implementation, and strategic decisions. • Adequacy of consumer education, safety, privacy, and protection is paramount. • Policy must maximise AMI benefits and minimise uncertainties, costs, and risks
Polany, Rany
2012-01-01
This research develops and applies an integrated hierarchical framework for modeling a multi-echelon supply chain network design, under the influence of demand uncertainty. The framework is a layered integration of two levels: macro, high-level scenario planning combined with micro, low-level Monte Carlo simulation of uncertainties in demand. To facilitate rapid simulation of the effects of demand uncertainty, the integrated framework was implemented as a dashboard automation system using Mic...
Typology of Uncertainties in the Development Process of Product-Service Systems
DEFF Research Database (Denmark)
Ramirez Hernandez, Tabea; Kreye, Melanie; Pigosso, Daniela Cristina Antelmi
This paper investigates uncertainty in the development of Product-Service Systems (PSS) – a complex combination of product and services. This research is important because practitioners struggle with managing the high uncertainties arising from the complexity of parallel product and service...... development in compound clusters of stakeholders. Yet, scholars have not analyzed these challenges extensively. Based on a combination of innovation management and servitization literature a conceptual framework is offered, detailing five uncertainty types relevant for PSS-development: environmental...
Discounting and the social cost of carbon: A closer look at uncertainty
Guo, J.K.; Hepburn, C.; Tol, R.S.J.; Anthoff, D.
2006-01-01
Recently, in the economics literature, several papers have put forward arguments for using a declining discount rate in social-cost benefit analysis. This paper examines the impact of employing a declining discount rate on the social cost of carbon-the marginal social damage from a ton of emitted
Cost effectiveness of recycling: A systems model
Energy Technology Data Exchange (ETDEWEB)
Tonjes, David J., E-mail: david.tonjes@stonybrook.edu [Department of Technology and Society, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, NY 11794-3560 (United States); Waste Reduction and Management Institute, School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY 11794-5000 (United States); Center for Bioenergy Research and Development, Advanced Energy Research and Technology Center, Stony Brook University, 1000 Innovation Rd., Stony Brook, NY 11794-6044 (United States); Mallikarjun, Sreekanth, E-mail: sreekanth.mallikarjun@stonybrook.edu [Department of Technology and Society, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, NY 11794-3560 (United States)
2013-11-15
Highlights: • Curbside collection of recyclables reduces overall system costs over a range of conditions. • When avoided costs for recyclables are large, even high collection costs are supported. • When avoided costs for recyclables are not great, there are reduced opportunities for savings. • For common waste compositions, maximizing curbside recyclables collection always saves money. - Abstract: Financial analytical models of waste management systems have often found that recycling costs exceed direct benefits, and in order to economically justify recycling activities, externalities such as household expenses or environmental impacts must be invoked. Certain more empirically based studies have also found that recycling is more expensive than disposal. Other work, both through models and surveys, have found differently. Here we present an empirical systems model, largely drawn from a suburban Long Island municipality. The model accounts for changes in distribution of effort as recycling tonnages displace disposal tonnages, and the seven different cases examined all show that curbside collection programs that manage up to between 31% and 37% of the waste stream should result in overall system savings. These savings accrue partially because of assumed cost differences in tip fees for recyclables and disposed wastes, and also because recycling can result in a more efficient, cost-effective collection program. These results imply that increases in recycling are justifiable due to cost-savings alone, not on more difficult to measure factors that may not impact program budgets.
Low cost metamodel for robust design of periodic nonlinear coupled micro-systems
Directory of Open Access Journals (Sweden)
Chikhaoui K.
2016-01-01
Full Text Available To achieve robust design, in presence of uncertainty, nonlinearity and structural periodicity, a metamodel combining the Latin Hypercube Sampling (LHS method for uncertainty propagation and an enriched Craig-Bampton Component Mode Synthesis approach (CB-CMS for model reduction is proposed. Its application to predict the time responses of a stochastic periodic nonlinear micro-system proves its efficiency in terms of accuracy and reduction of computational cost.
Jin, Shan
This dissertation concerns power system expansion planning under different market mechanisms. The thesis follows a three paper format, in which each paper emphasizes a different perspective. The first paper investigates the impact of market uncertainties on a long term centralized generation expansion planning problem. The problem is modeled as a two-stage stochastic program with uncertain fuel prices and demands, which are represented as probabilistic scenario paths in a multi-period tree. Two measurements, expected cost (EC) and Conditional Value-at-Risk (CVaR), are used to minimize, respectively, the total expected cost among scenarios and the risk of incurring high costs in unfavorable scenarios. We sample paths from the scenario tree to reduce the problem scale and determine the sufficient number of scenarios by computing confidence intervals on the objective values. The second paper studies an integrated electricity supply system including generation, transmission and fuel transportation with a restructured wholesale electricity market. This integrated system expansion problem is modeled as a bi-level program in which a centralized system expansion decision is made in the upper level and the operational decisions of multiple market participants are made in the lower level. The difficulty of solving a bi-level programming problem to global optimality is discussed and three problem relaxations obtained by reformulation are explored. The third paper solves a more realistic market-based generation and transmission expansion problem. It focuses on interactions among a centralized transmission expansion decision and decentralized generation expansion decisions. It allows each generator to make its own strategic investment and operational decisions both in response to a transmission expansion decision and in anticipation of a market price settled by an Independent System Operator (ISO) market clearing problem. The model poses a complicated tri-level structure
Computational uncertainties in silicon dioxide/plutonium intermediate neutron spectrum systems
International Nuclear Information System (INIS)
Jaegers, P.J.
1997-01-01
In the past several years, several proposals have been made for the long-term stabilization and storage of surplus fissile materials. Many of these proposed scenarios involve systems that have an intermediate neutron energy spectrum. Such intermediate-energy systems are dominated by scattering and fission events induced by neutrons ranging in energy from 1 eV to 100keV. To ensure adequate safety margins and cost effectiveness, it is necessary to have benchmark data for these intermediate-energy spectrum systems; however, a review of the nuclear criticality benchmarks indicates that no formal benchmarks are available. Nuclear data uncertainties have been reported for some types of intermediate-energy spectrum systems. Using a variety of Monte Carlo computer codes and cross-section sets, reported significant variations in the calculated k ∞ of intermediate-energy spectrum metal/ 235 U systems. We discuss the characteristics of intermediate neutron spectrum systems and some of the computational differences that can occur in calculating the k eff of these systems
Cost benefit analysis of reactor safety systems
International Nuclear Information System (INIS)
Maurer, H.A.
1984-01-01
Cost/benefit analysis of reactor safety systems is a possibility appropriate to deal with reactor safety. The Commission of the European Communities supported a study on the cost-benefit or cost effectiveness of safety systems installed in modern PWR nuclear power plants. The following systems and their cooperation in emergency cases were in particular investigated in this study: the containment system (double containment), the leakage exhaust and control system, the annulus release exhaust system and the containment spray system. The benefit of a safety system is defined according to its contribution to the reduction of the radiological consequences for the environment after a LOCA. The analysis is so far performed in two different steps: the emergency core cooling system is considered to function properly, failure of the emergency core cooling system is assumed (with the possible consequence of core melt-down) and the results may demonstrate the evidence that striving for cost-effectiveness can produce a safer end result than the philosophy of safety at any cost. (orig.)
Optimal operation method coping with uncertainty in multi-area small power systems
Directory of Open Access Journals (Sweden)
Shota Tobaru
2017-07-01
Full Text Available Japan contains a vast number of isolated islands. Majority of these islands are poweredby diesel generators (DGs, which are operationally not economical. Therefore, the introduction of renewableenergy systems (RESs into these area is very much vital. However, the variability of RESs asa result of weather condition as well as load demand , battery energy storage system (BESS is broughtinto play. Demand response (DR programs have also been so attractive in the energy management systemsfor the past decades. Among them, the real-time pricing (RTP has been one of the most effectivedemand response program being utilized. This program encourages the customer to increase or reducethe load consumption by varying the electricity price. Also, due to the increase in power transactionmarket, Japan electric power exchange (JEPX has established spot (day-ahead, intraday hour-ahead,and forward market programs. This paper utilizes day-ahead and hour-ahead markets, since these marketscan make it possible to deal with uncertainty related to generated power fluctuations. Therefore,this paper presents the optimal operation method coping with the uncertainties of RESs in multi-areasmall power systems. The proposed method enables flexibility to correspond to the forecasting error byproviding two kinds of power markets among multi-area small power systems and trading the shortageand surplus powers. Furthermore, it accomplishes a stable power supply and demand by RTP. Thus, theproposed method was able to reduce operational cost for multi-area small power systems. The processof creating operational plan for RTP, power trading at the markets and the unit commitment of DGs arealso presented in this paper. Simulation results corroborate the merit of the proposed program.
Accounting for data uncertainties in comparing risks from energy systems
International Nuclear Information System (INIS)
Hauptmanns, Ulrich
1998-01-01
Data and models for risk comparisons are uncertain and this is true all the more the larger the time horizon contemplated. Statistical methods are presented for dealing with data uncertainties thus providing a broader foundation for decisions. Nevertheless, it has to be borne in mind that no method exists to account for the 'unforeseeable' which is always present in decision making with respect to the far future. (author)
INTEGRATION OF SYSTEM COMPONENTS AND UNCERTAINTY ANALYSIS - HANFORD EXAMPLES
International Nuclear Information System (INIS)
Wood, M.I.
2009-01-01
(sm b ullet) Deterministic 'One Off' analyses as basis for evaluating sensitivity and uncertainty relative to reference case (sm b ullet) Spatial coverage identical to reference case (sm b ullet) Two types of analysis assumptions - Minimax parameter values around reference case conditions - 'What If' cases that change reference case condition and associated parameter values (sm b ullet) No conclusions about likelihood of estimated result other than' qualitative expectation that actual outcome should tend toward reference case estimate
Minimum Cost Nanosatellite Launch System, Phase I
National Aeronautics and Space Administration — Delta Velocity Corporation proposes the development of a very low cost, highly responsive nanosat launch system. We propose to develop an integrated propulsion...
Directory of Open Access Journals (Sweden)
Vahid Raissi Dehkordi
2009-01-01
Full Text Available This paper deals with the robust performance problem of a linear time-invariant control system in the presence of robust controller uncertainty. Assuming that plant uncertainty is modeled as an additive perturbation, a geometrical approach is followed in order to find a necessary and sufficient condition for robust performance in the form of a bound on the magnitude of controller uncertainty. This frequency domain bound is derived by converting the problem into an optimization problem, whose solution is shown to be more time-efficient than a conventional structured singular value calculation. The bound on controller uncertainty can be used in controller order reduction and implementation problems.
Chen, Ho-Wen; Chang, Ni-Bin
2002-08-01
Prediction of construction cost of wastewater treatment facilities could be influential for the economic feasibility of various levels of water pollution control programs. However, construction cost estimation is difficult to precisely evaluate in an uncertain environment and measured quantities are always burdened with different types of cost structures. Therefore, an understanding of the previous development of wastewater treatment plants and of the related construction cost structures of those facilities becomes essential for dealing with an effective regional water pollution control program. But deviations between the observed values and the estimated values are supposed to be due to measurement errors only in the conventional regression models. The inherent uncertainties of the underlying cost structure, where the human estimation is influential, are rarely explored. This paper is designed to recast a well-known problem of construction cost estimation for both domestic and industrial wastewater treatment plants via a comparative framework. Comparisons were made for three technologies of regression analyses, including the conventional least squares regression method, the fuzzy linear regression method, and the newly derived fuzzy goal regression method. The case study, incorporating a complete database with 48 domestic wastewater treatment plants and 29 industrial wastewater treatment plants being collected in Taiwan, implements such a cost estimation procedure in an uncertain environment. Given that the fuzzy structure in regression estimation may account for the inherent human complexity in cost estimation, the fuzzy goal regression method does exhibit more robust results in terms of some criteria. Moderate economy of scale exists in constructing both the domestic and industrial wastewater treatment plants. Findings indicate that the optimal size of a domestic wastewater treatment plant is approximately equivalent to 15,000 m3/day (CMD) and higher in Taiwan
Cost and effectiveness of radon barrier systems
International Nuclear Information System (INIS)
Baker, E.G.; Freeman, H.D.; Hartley, J.N.; Gee, G.W.
1982-12-01
Earthen, asphalt, and multilayer radon barrier systems can all provide reduction in the amount of radon gas released from uranium mill tailings. Pacific Northwest Laboratory field tested all three types of covers at Grand Junction, Colorado during the summer of 1981. All nine individual radon barrier systems tested currently meet the EPA standard for radon flux of 20 pCi m - 2 s - 1 . The cost of the asphalt and 3m earthen covers were about the same at the field test. Multilayer covers were significantly more costly. Cost estimates for three high priority western sites indicate 3m of earthen cover is the least costly radon barrier when earthen material is available at or near the disposal site. If earthen material must be imported more than 8 to 10 km asphalt and possibly multilayer radon barriers can be cost effective
Chen, Peng-Fei; Sun, Wen-Yang; Ming, Fei; Huang, Ai-Jun; Wang, Dong; Ye, Liu
2018-01-01
Quantum objects are susceptible to noise from their surrounding environments, interaction with which inevitably gives rise to quantum decoherence or dissipation effects. In this work, we examine how different types of local noise under an open system affect entropic uncertainty relations for two incompatible measurements. Explicitly, we observe the dynamics of the entropic uncertainty in the presence of quantum memory under two canonical categories of noisy environments: unital (phase flip) and nonunital (amplitude damping). Our study shows that the measurement uncertainty exhibits a non-monotonic dynamical behavior—that is, the amount of the uncertainty will first inflate, and subsequently decrease, with the growth of decoherence strengths in the two channels. In contrast, the uncertainty decreases monotonically with the growth of the purity of the initial state shared in prior. In order to reduce the measurement uncertainty in noisy environments, we put forward a remarkably effective strategy to steer the magnitude of uncertainty by means of a local non-unitary operation (i.e. weak measurement) on the qubit of interest. It turns out that this non-unitary operation can greatly reduce the entropic uncertainty, upon tuning the operation strength. Our investigations might thereby offer an insight into the dynamics and steering of entropic uncertainty in open systems.
Moment based model predictive control for systems with additive uncertainty
Saltik, M.B.; Ozkan, L.; Weiland, S.; Ludlage, J.H.A.
2017-01-01
In this paper, we present a model predictive control (MPC) strategy based on the moments of the state variables and the cost functional. The statistical properties of the state predictions are calculated through the open loop iteration of dynamics and used in the formulation of MPC cost function. We
Users manual for the FORSS sensitivity and uncertainty analysis code system
International Nuclear Information System (INIS)
Lucius, J.L.; Weisbin, C.R.; Marable, J.H.; Drischler, J.D.; Wright, R.Q.; White, J.E.
1981-01-01
FORSS is a code system used to study relationships between nuclear reaction cross sections, integral experiments, reactor performance parameter predictions and associated uncertainties. This report describes the computing environment and the modules currently used to implement FORSS Sensitivity and Uncertainty Methodology
Users manual for the FORSS sensitivity and uncertainty analysis code system
Energy Technology Data Exchange (ETDEWEB)
Lucius, J.L.; Weisbin, C.R.; Marable, J.H.; Drischler, J.D.; Wright, R.Q.; White, J.E.
1981-01-01
FORSS is a code system used to study relationships between nuclear reaction cross sections, integral experiments, reactor performance parameter predictions and associated uncertainties. This report describes the computing environment and the modules currently used to implement FORSS Sensitivity and Uncertainty Methodology.
Development of cost-benefit analysis system
International Nuclear Information System (INIS)
Shiba, Tsuyoshi; Mishima, Tetsuya; Yuyama, Tomonori; Suzuki, Atsushi
2001-01-01
In order to promote the FDR development, it is necessary to see various benefits brought by introduction of FBR from multiple perspectives and have a good grasp of such benefits quantitatively and an adequate R and D investment scale which corresponds with them. In this study, the structured prototype in the previous study was improved to be able to perform cost-benefit analysis. An example of improvement made in the system is addition of subroutine used for comparison between new energy and benefits brought by introduction of FBR with special emphasis on addition of logic for analyzing externality about the new energy. Other improvement examples are modification of the Conventional Year Expense Ratio method of power generation cost to Average Durable Year Cost method, addition of database function and turning input data into database, and reviewing idea on cost by the type of waste material and price of uranium. The cost-benefit analysis system was also restructured utilizing Microsoft ACCESS so that it should have a data base function. As the result of the improvement mentioned above, we expect that the improved cost-benefit analysis system will have higher generality than the system before; therefore, great deal of benefits brought by application of the system in the future is expected. (author)
Directory of Open Access Journals (Sweden)
Ryusuke Konishi
2018-01-01
Full Text Available In deregulated electricity markets, minimizing the procurement costs of electricity is a critical problem for procurement agencies (PAs. However, uncertainty is inevitable for PAs and includes multiple factors such as market prices, photovoltaic system (PV output and demand. This study focuses on settlements in multi-period markets (a day-ahead market and a real-time market and the installation of energy storage systems (ESSs. ESSs can be utilized for time arbitrage in the day-ahead market and to reduce the purchasing/selling of electricity in the real-time market. However, the high costs of an ESS mean the size of the system needs to be minimized. In addition, when determining the size of an ESS, it is important to identify the size appropriate for each role. Therefore, we employ the concept of a “slow” and a “fast” ESS to quantify the size of a system’s role, based on the values associated with the various uncertainties. Because the problem includes nonlinearity and non-convexity, we solve it within a realistic computational burden by reformulating the problem using reasonable assumptions. Therefore, this study identifies the optimal sizes of ESSs and procurement, taking into account the uncertainties of prices in multi-period markets, PV output and demand.
Verification and uncertainty evaluation of HELIOS/MASTER nuclear design system
Energy Technology Data Exchange (ETDEWEB)
Song, Jae Seung; Kim, J. C.; Cho, B. O. [Korea Atomic Energy Research Institute, Taejon (Korea)
1999-03-01
A nuclear design system HELIOS/MASTER was established and core follow calculations were performed for Yonggwang Unit 1 cycles 1 through 7 and Yonggwang Unit 3 cycles 1 through 2. The accuracy of HELIOS/MASTER system was evaluated by estimations of uncertainties of reactivity and peaking factors and by comparisons of the maximum differences of isothermal temperature coefficient, inverse boron worth and control rod worth with the CASMO-3/MASTER uncertainties. The reactivity uncertainty was estimated by 362 pcm, and the uncertainties of three-dimensional, axially integrated radial, and planar peaking factors were evaluated by 0.048, 0.034, and 0.044 in relative power unit, respectively. The maximum differences of isothermal temperature coefficient, inverse boron worth and control rod worth were within the CASMO-3/MASTER uncertainties. 17 refs., 17 figs., 10 tabs. (Author)
Development of Uncertainty Analysis Method for SMART Digital Core Protection and Monitoring System
International Nuclear Information System (INIS)
Koo, Bon Seung; In, Wang Kee; Hwang, Dae Hyun
2012-01-01
The Korea Atomic Energy Research Institute has developed a system-integrated modular advanced reactor (SMART) for a seawater desalination and electricity generation. Online digital core protection and monitoring systems, called SCOPS and SCOMS respectively were developed. SCOPS calculates minimum DNBR and maximum LPD based on the several online measured system parameters. SCOMS calculates the variables of limiting conditions for operation. KAERI developed overall uncertainty analysis methodology which is used statistically combining uncertainty components of SMART core protection and monitoring system. By applying overall uncertainty factors in on-line SCOPS/SCOMS calculation, calculated LPD and DNBR are conservative with a 95/95 probability/confidence level. In this paper, uncertainty analysis method is described for SMART core protection and monitoring system
Energy Technology Data Exchange (ETDEWEB)
Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.
2010-09-01
The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation) and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. In order to improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively, by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique
Implementation of unscented transform to estimate the uncertainty of a liquid flow standard system
Energy Technology Data Exchange (ETDEWEB)
Chun, Sejong; Choi, Hae-Man; Yoon, Byung-Ro; Kang, Woong [Korea Research Institute of Standards and Science, Daejeon (Korea, Republic of)
2017-03-15
First-order partial derivatives of a mathematical model are an essential part of evaluating the measurement uncertainty of a liquid flow standard system according to the Guide to the expression of uncertainty in measurement (GUM). Although the GUM provides a straightforward method to evaluate the measurement uncertainty of volume flow rate, the first-order partial derivatives can be complicated. The mathematical model of volume flow rate in a liquid flow standard system has a cross-correlation between liquid density and buoyancy correction factor. This cross-correlation can make derivation of the first-order partial derivatives difficult. Monte Carlo simulation can be used as an alternative method to circumvent the difficulty in partial derivation. However, the Monte Carlo simulation requires large computational resources for a correct simulation because it considers the completeness issue whether an ideal or a real operator conducts an experiment to evaluate the measurement uncertainty. Thus, the Monte Carlo simulation needs a large number of samples to ensure that the uncertainty evaluation is as close to the GUM as possible. Unscented transform can alleviate this problem because unscented transform can be regarded as a Monte Carlo simulation with an infinite number of samples. This idea means that unscented transform considers the uncertainty evaluation with respect to the ideal operator. Thus, unscented transform can evaluate the measurement uncertainty the same as the uncertainty that the GUM provides.
A cost modelling system for cloud computing
Ajeh, Daniel; Ellman, Jeremy; Keogh, Shelagh
2014-01-01
An advance in technology unlocks new opportunities for organizations to increase their productivity, efficiency and process automation while reducing the cost of doing business as well. The emergence of cloud computing addresses these prospects through the provision of agile systems that are scalable, flexible and reliable as well as cost effective. Cloud computing has made hosting and deployment of computing resources cheaper and easier with no up-front charges but pay per-use flexible payme...
Roles of nuclear power system in the presence of uncertainties from global warming
International Nuclear Information System (INIS)
Kiriyama, Eriko; Iwata, Shuichi
2005-01-01
Environmental 'bads' like carbon dioxide are not simply incorporated in the market system. The costs involved, however, do not really reflect the inherent value of the environment, or what it is worth to them. This study focuses on the uncertainty of CO 2 emission credits. Assigning economic values to environmental goods and services is complex, but it is an area that is receiving considerable attention from environmental economists. The purpose of this study is to analyze the value of an investment in power generation assets that do not emit CO 2 . To deal with the CO 2 emission credit, we built new models based on the real option model by Pindyck (2000). In the modern, market-based financial systems that dominate the global economy, the value of a resource is represented by the price that an individual or a group is willing to pay for it. Managing CO 2 emission limitations will be a critical aspect of power generation systems. And it will be increasingly so as the emphasis on global environmental issues continues to rise. In order to secure the effectiveness of measures against global warming, we should reconsider the role of nuclear power systems. (author)
Using cost/risk uncertainty spheres to make better environmental restoration decisions
International Nuclear Information System (INIS)
Shangraw, R.F.; Cheney, C.S.; Shangraw, W.R.
1994-01-01
The process of balancing cost expenditures and risk reductions during environmental restoration (ER) activities (and as part of other environmental programs such as waste management and facility transition) is the critical policy decision facing DOE site decisionmakers and associated stakeholders (including regulators). The ground rules for this process are specified formally in the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), as amended, the Resource Conservation and Recovery Act, as amended, the subsequent regulations (e.g., National Contingency Plan) and policies that EPA and State agencies have issued to implement these programs, and (increasingly) interagency agreements and orders. Clearly, as Federal resources to meet environmental commitments become more constrained, cost and risk management tradeoffs will become even more needed and their results pronounced
International Nuclear Information System (INIS)
Chen, Hao; Kang, Jia-Ning; Liao, Hua; Tang, Bao-Jun; Wei, Yi-Ming
2017-01-01
Energy conservation technologies in the coal-fired power sector are important solutions for the environmental pollution and climate change issues. However, a unified framework for estimating their costs and potentials is still needed due to the wide technology choices, especially considering their economic feasibility under fuel and carbon price uncertainties. Therefore, this study has employed a bottom-up approach to analyze the costs and potentials of 32 key technologies’ new promotions during the 13th Five-Year Plan period (2016–2020), which combines the conservation supply curve (CSC) approach and break-even analysis. Findings show that (1) these 32 technologies have a total coal conservation potential of 275.77 Mt with a cost of 238.82 billion yuan, and their break-even coal price is 866 yuan/ton. (2) steam-water circulation system has the largest energy conservation potential in the coal-fired power industry. (3) considering the co-benefits will facilitate these technologies’ promotions, because their break-even coal prices will decrease by 2.35 yuan/ton when the carbon prices increase by 1 yuan/ton. (4) discount rates have the largest impacts on the technologies’ cost-effectiveness, while the future generation level affect their energy conservation potentials most. - Highlights: • The 32 technologies can save 275.77 Mt coal with a cost of 238.82 billion yuan. • The steam-water circulation system has the largest energy conservation potential. • Considering the co-benefits will facilitate the technology promotions • Discount rates have the largest impacts on the technologies’ cost-effectiveness.
Preliminary Uncertainty Analysis for SMART Digital Core Protection and Monitoring System
International Nuclear Information System (INIS)
Koo, Bon Seung; In, Wang Kee; Hwang, Dae Hyun
2012-01-01
The Korea Atomic Energy Research Institute (KAERI) developed on-line digital core protection and monitoring systems, called SCOPS and SCOMS as a part of SMART plant protection and monitoring system. SCOPS simplified the protection system by directly connecting the four RSPT signals to each core protection channel and eliminated the control element assembly calculator (CEAC) hardware. SCOMS adopted DPCM3D method in synthesizing core power distribution instead of Fourier expansion method being used in conventional PWRs. The DPCM3D method produces a synthetic 3-D power distribution by coupling a neutronics code and measured in-core detector signals. The overall uncertainty analysis methodology which is used statistically combining uncertainty components of SMART core protection and monitoring system was developed. In this paper, preliminary overall uncertainty factors for SCOPS/SCOMS of SMART initial core were evaluated by applying newly developed uncertainty analysis method
National Aeronautics and Space Administration — We propose to develop a new system for quantitative assessment of uncertainties in LEO satellite position caused by storm time changes in space environmental...
Understanding uncertainty propagation in life cycle assessments of waste management systems
DEFF Research Database (Denmark)
Bisinella, Valentina; Conradsen, Knut; Christensen, Thomas Højlund
2015-01-01
Uncertainty analysis in Life Cycle Assessments (LCAs) of waste management systems often results obscure and complex, with key parameters rarely determined on a case-by-case basis. The paper shows an application of a simplified approach to uncertainty coupled with a Global Sensitivity Analysis (GSA......) perspective on three alternative waste management systems for Danish single-family household waste. The approach provides a fast and systematic method to select the most important parameters in the LCAs, understand their propagation and contribution to uncertainty....
[Relationship between cost systems and hospital expenditure].
García-Cornejo, Beatriz; Pérez-Méndez, José A
To analyze the relationship between the degree of development of hospital cost systems (CS) implemented by the regional health services (RHS) and the variation in unit cost of hospitals in Spanish National Health Service (NHS) between 2010 and 2013 and to identify other explanatory factors of this variation. A database of NHS hospitals was constructed from exclusively public sources. Using a multilevel regression model, explaining factors of the variation in unit cost (cost per weighted unit of activity [WAU]) of a sample of 170 hospitals were analyzed. The variables representative of the degree of development of CS are associated in a negative and significant way with the variation of the cost per WAU. It is observed that if a high-level development CS is used the cost variation per WAU would be reduced by close to 3.2%. There is also a negative and significant relationship between the variation in the cost per WAU and the variations in the percentage of high technology and the hospital occupancy rate. On the other hand, the variations in the average cost of personnel and in the number of workers per 100 beds are associated in a positive and significant way with the variation of the cost per WAU. In the period analysed, during which the main health expenditure adjustment was made, the control in hospital unit cost is associated not only with spending cuts but also with aspects related to their management, such as the implementation of more developed CS. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.
International Nuclear Information System (INIS)
Rajagopalan, C.; Kalyanasundaram, P.; Baldev Raj
1996-01-01
The use of fuzzy logic, as a framework for uncertainty management, in a knowledge-based system (KBS) for ultrasonic testing of austenitic stainless steels is described. Parameters that may contain uncertain values are identified. Methodologies to handle uncertainty in these parameters using fuzzy logic are detailed. The overall improvement in the performance of the knowledge-based system after incorporating fuzzy logic is discussed. The methodology developed being universal, its extension to other KBS for nondestructive testing and evaluation is highlighted. (author)
Final Report: Hydrogen Storage System Cost Analysis
Energy Technology Data Exchange (ETDEWEB)
James, Brian David [Strategic Analysis Inc., Arlington, VA (United States); Houchins, Cassidy [Strategic Analysis Inc., Arlington, VA (United States); Huya-Kouadio, Jennie Moton [Strategic Analysis Inc., Arlington, VA (United States); DeSantis, Daniel A. [Strategic Analysis Inc., Arlington, VA (United States)
2016-09-30
The Fuel Cell Technologies Office (FCTO) has identified hydrogen storage as a key enabling technology for advancing hydrogen and fuel cell power technologies in transportation, stationary, and portable applications. Consequently, FCTO has established targets to chart the progress of developing and demonstrating viable hydrogen storage technologies for transportation and stationary applications. This cost assessment project supports the overall FCTO goals by identifying the current technology system components, performance levels, and manufacturing/assembly techniques most likely to lead to the lowest system storage cost. Furthermore, the project forecasts the cost of these systems at a variety of annual manufacturing rates to allow comparison to the overall 2017 and “Ultimate” DOE cost targets. The cost breakdown of the system components and manufacturing steps can then be used to guide future research and development (R&D) decisions. The project was led by Strategic Analysis Inc. (SA) and aided by Rajesh Ahluwalia and Thanh Hua from Argonne National Laboratory (ANL) and Lin Simpson at the National Renewable Energy Laboratory (NREL). Since SA coordinated the project activities of all three organizations, this report includes a technical description of all project activity. This report represents a summary of contract activities and findings under SA’s five year contract to the US Department of Energy (Award No. DE-EE0005253) and constitutes the “Final Scientific Report” deliverable. Project publications and presentations are listed in the Appendix.
Distribution system costs associated with the deployment of photovoltaic systems
Energy Technology Data Exchange (ETDEWEB)
Horowitz, Kelsey A. W.; Palmintier, Bryan; Mather, Barry; Denholm, Paul
2018-07-01
The broadening of our energy system to include increasing amounts of wind and solar has led to significant debate about the total costs and benefits associated with different types of generators - with potentially far-reaching policy implications. This has included debate about the cost associated with integrating these generators onto the electric grid. For photovoltaics (PV), this encompasses costs incurred on both the bulk power and distribution systems, as well as the value provided to them. These costs and benefits, in particular those associated with integrating PV onto the distribution system, are not well understood. We seek to advance the state of understanding of 'grid integration costs' for the distribution system by reviewing prior literature and outlining a transparent, bottom-up approach that can be used to calculate these costs. We provide a clear delineation of costs to integrate PV in to the distribution system within the larger context of total costs and benefits associated with PV generators. We emphasize that these costs are situationally dependent, and that a single 'cost of integration' cannot be obtained. We additionally emphasize that benefits must be considered when evaluating the competitiveness of the technology in a given situation.
Integrated waste management system costs in a MPC system
International Nuclear Information System (INIS)
Supko, E.M.
1995-01-01
The impact on system costs of including a centralized interim storage facility as part of an integrated waste management system based on multi-purpose canister (MPC) technology was assessed in analyses by Energy Resources International, Inc. A system cost savings of $1 to $2 billion occurs if the Department of Energy begins spent fuel acceptance in 1998 at a centralized interim storage facility. That is, the savings associated with decreased utility spent fuel management costs will be greater than the cost of constructing and operating a centralized interim storage facility
Application of fuzzy system theory in addressing the presence of uncertainties
Energy Technology Data Exchange (ETDEWEB)
Yusmye, A. Y. N. [Institute of Engineering Mathematics, Universiti Malaysia Perlis Kampus Pauh Putra, 02600, Arau, Perlis (Malaysia); Goh, B. Y.; Adnan, N. F.; Ariffin, A. K. [Department of Mechanical and Materials, Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia 43600 UKM Bangi, Selangor (Malaysia)
2015-02-03
In this paper, the combinations of fuzzy system theory with the finite element methods are present and discuss to deal with the uncertainties. The present of uncertainties is needed to avoid for prevent the failure of the material in engineering. There are three types of uncertainties, which are stochastic, epistemic and error uncertainties. In this paper, the epistemic uncertainties have been considered. For the epistemic uncertainty, it exists as a result of incomplete information and lack of knowledge or data. Fuzzy system theory is a non-probabilistic method, and this method is most appropriate to interpret the uncertainty compared to statistical approach when the deal with the lack of data. Fuzzy system theory contains a number of processes started from converting the crisp input to fuzzy input through fuzzification process and followed by the main process known as mapping process. The term mapping here means that the logical relationship between two or more entities. In this study, the fuzzy inputs are numerically integrated based on extension principle method. In the final stage, the defuzzification process is implemented. Defuzzification is an important process to allow the conversion of the fuzzy output to crisp outputs. Several illustrative examples are given and from the simulation, the result showed that propose the method produces more conservative results comparing with the conventional finite element method.
Application of fuzzy system theory in addressing the presence of uncertainties
International Nuclear Information System (INIS)
Yusmye, A. Y. N.; Goh, B. Y.; Adnan, N. F.; Ariffin, A. K.
2015-01-01
In this paper, the combinations of fuzzy system theory with the finite element methods are present and discuss to deal with the uncertainties. The present of uncertainties is needed to avoid for prevent the failure of the material in engineering. There are three types of uncertainties, which are stochastic, epistemic and error uncertainties. In this paper, the epistemic uncertainties have been considered. For the epistemic uncertainty, it exists as a result of incomplete information and lack of knowledge or data. Fuzzy system theory is a non-probabilistic method, and this method is most appropriate to interpret the uncertainty compared to statistical approach when the deal with the lack of data. Fuzzy system theory contains a number of processes started from converting the crisp input to fuzzy input through fuzzification process and followed by the main process known as mapping process. The term mapping here means that the logical relationship between two or more entities. In this study, the fuzzy inputs are numerically integrated based on extension principle method. In the final stage, the defuzzification process is implemented. Defuzzification is an important process to allow the conversion of the fuzzy output to crisp outputs. Several illustrative examples are given and from the simulation, the result showed that propose the method produces more conservative results comparing with the conventional finite element method
Energy Technology Data Exchange (ETDEWEB)
Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.
2010-01-01
The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter
Analysis of uncertainties in the IAEA/WHO TLD postal dose audit system
Energy Technology Data Exchange (ETDEWEB)
Izewska, J. [Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Wagramer Strasse 5, Vienna (Austria)], E-mail: j.izewska@iaea.org; Hultqvist, M. [Department of Medical Radiation Physics, Karolinska Institute, Stockholm University, Stockholm (Sweden); Bera, P. [Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Wagramer Strasse 5, Vienna (Austria)
2008-02-15
The International Atomic Energy Agency (IAEA) and the World Health Organisation (WHO) operate the IAEA/WHO TLD postal dose audit programme. Thermoluminescence dosimeters (TLDs) are used as transfer devices in this programme. In the present work the uncertainties in the dose determination from TLD measurements have been evaluated. The analysis of uncertainties comprises uncertainties in the calibration coefficient of the TLD system and uncertainties in factors correcting for dose response non-linearity, fading of TL signal, energy response and influence of TLD holder. The individual uncertainties have been combined to estimate the total uncertainty in the dose evaluated from TLD measurements. The combined relative standard uncertainty in the dose determined from TLD measurements has been estimated to be 1.2% for irradiations with Co-60 {gamma}-rays and 1.6% for irradiations with high-energy X-rays. Results from irradiations by the Bureau international des poids et mesures (BIPM), Primary Standard Dosimetry Laboratories (PSDLs) and Secondary Standards Dosimetry Laboratories (SSDLs) compare favourably with the estimated uncertainties, whereas TLD results of radiotherapy centres show higher standard deviations than those derived theoretically.
Controversies Regarding Costs, Uncertainties and Benefits Specific to Shale Gas Development
Directory of Open Access Journals (Sweden)
Jianu Daniel Muresan
2015-03-01
Full Text Available The shale gas exploration and development is now a delicate and controversial subject. It is often assumed that unconventional exploration and extraction automatically brings prosperity for local, national and regional economies. In this paper, we argue that shale gas development requires a contextualized understanding of regional issues. We are also trying to identify the opportunities and the risks of shale gas development in Eastern Europe (referring to Romania’s case and offer a cost-benefit analysis model that may be of interest to any policymakers and investors.
Elbasha, Elamin H
2005-05-01
The availability of patient-level data from clinical trials has spurred a lot of interest in developing methods for quantifying and presenting uncertainty in cost-effectiveness analysis (CEA). Although the majority has focused on developing methods for using sample data to estimate a confidence interval for an incremental cost-effectiveness ratio (ICER), a small strand of the literature has emphasized the importance of incorporating risk preferences and the trade-off between the mean and the variance of returns to investment in health and medicine (mean-variance analysis). This paper shows how the exponential utility-moment-generating function approach is a natural extension to this branch of the literature for modelling choices from healthcare interventions with uncertain costs and effects. The paper assumes an exponential utility function, which implies constant absolute risk aversion, and is based on the fact that the expected value of this function results in a convenient expression that depends only on the moment-generating function of the random variables. The mean-variance approach is shown to be a special case of this more general framework. The paper characterizes the solution to the resource allocation problem using standard optimization techniques and derives the summary measure researchers need to estimate for each programme, when the assumption of risk neutrality does not hold, and compares it to the standard incremental cost-effectiveness ratio. The importance of choosing the correct distribution of costs and effects and the issues related to estimation of the parameters of the distribution are also discussed. An empirical example to illustrate the methods and concepts is provided. Copyright 2004 John Wiley & Sons, Ltd
Using finite mixture models in thermal-hydraulics system code uncertainty analysis
Energy Technology Data Exchange (ETDEWEB)
Carlos, S., E-mail: scarlos@iqn.upv.es [Department d’Enginyeria Química i Nuclear, Universitat Politècnica de València, Camí de Vera s.n, 46022 València (Spain); Sánchez, A. [Department d’Estadística Aplicada i Qualitat, Universitat Politècnica de València, Camí de Vera s.n, 46022 València (Spain); Ginestar, D. [Department de Matemàtica Aplicada, Universitat Politècnica de València, Camí de Vera s.n, 46022 València (Spain); Martorell, S. [Department d’Enginyeria Química i Nuclear, Universitat Politècnica de València, Camí de Vera s.n, 46022 València (Spain)
2013-09-15
Highlights: • Best estimate codes simulation needs uncertainty quantification. • The output variables can present multimodal probability distributions. • The analysis of multimodal distribution is performed using finite mixture models. • Two methods to reconstruct output variable probability distribution are used. -- Abstract: Nuclear Power Plant safety analysis is mainly based on the use of best estimate (BE) codes that predict the plant behavior under normal or accidental conditions. As the BE codes introduce uncertainties due to uncertainty in input parameters and modeling, it is necessary to perform uncertainty assessment (UA), and eventually sensitivity analysis (SA), of the results obtained. These analyses are part of the appropriate treatment of uncertainties imposed by current regulation based on the adoption of the best estimate plus uncertainty (BEPU) approach. The most popular approach for uncertainty assessment, based on Wilks’ method, obtains a tolerance/confidence interval, but it does not completely characterize the output variable behavior, which is required for an extended UA and SA. However, the development of standard UA and SA impose high computational cost due to the large number of simulations needed. In order to obtain more information about the output variable and, at the same time, to keep computational cost as low as possible, there has been a recent shift toward developing metamodels (model of model), or surrogate models, that approximate or emulate complex computer codes. In this way, there exist different techniques to reconstruct the probability distribution using the information provided by a sample of values as, for example, the finite mixture models. In this paper, the Expectation Maximization and the k-means algorithms are used to obtain a finite mixture model that reconstructs the output variable probability distribution from data obtained with RELAP-5 simulations. Both methodologies have been applied to a separated
Cost estimating issues in the Russian integrated system planning context
International Nuclear Information System (INIS)
Allentuck, J.
1996-01-01
An important factor in the credibility of an optimal capacity expansion plan is the accuracy of cost estimates given the uncertainty of future economic conditions. This paper examines the problems associated with estimating investment and operating costs in the Russian nuclear power context over the period 1994 to 2010
Uncertainty analysis technique of dynamic response and cumulative damage properties of piping system
International Nuclear Information System (INIS)
Suzuki, Kohei; Aoki, Shigeru; Hara, Fumio; Hanaoka, Masaaki; Yamashita, Tadashi.
1982-01-01
It is a technologically important subject to establish the method of uncertainty analysis statistically examining the variation of the earthquake response and damage properties of equipment and piping system due to the change of input load and the parameters of structural system, for evaluating the aseismatic capability and dynamic structural reliability of these systems. The uncertainty in the response and damage properties when equipment and piping system are subjected to excessive vibration load is mainly dependent on the irregularity of acting input load such as the unsteady vibration of earthquakes, and structural uncertainty in forms and dimensions. This study is the basic one to establish the method for evaluating the uncertainty in the cumulative damage property at the time of resonant vibration of piping system due to the disperse of structural parameters with a simple model. First, the piping models with simple form were broken by resonant vibration, and the uncertainty in the cumulative damage property was evaluated. Next, the response analysis using an elasto-plastic mechanics model was performed by numerical simulation. Finally, the method of uncertainty analysis for response and damage properties by the perturbation method utilizing equivalent linearization was proposed, and its propriety was proved. (Kako, I.)
Modeling Multibody Systems with Uncertainties. Part I: Theoretical and Computational Aspects
International Nuclear Information System (INIS)
Sandu, Adrian; Sandu, Corina; Ahmadian, Mehdi
2006-01-01
This study explores the use of generalized polynomial chaos theory for modeling complex nonlinear multibody dynamic systems in the presence of parametric and external uncertainty. The polynomial chaos framework has been chosen because it offers an efficient computational approach for the large, nonlinear multibody models of engineering systems of interest, where the number of uncertain parameters is relatively small, while the magnitude of uncertainties can be very large (e.g., vehicle-soil interaction). The proposed methodology allows the quantification of uncertainty distributions in both time and frequency domains, and enables the simulations of multibody systems to produce results with 'error bars'. The first part of this study presents the theoretical and computational aspects of the polynomial chaos methodology. Both unconstrained and constrained formulations of multibody dynamics are considered. Direct stochastic collocation is proposed as less expensive alternative to the traditional Galerkin approach. It is established that stochastic collocation is equivalent to a stochastic response surface approach. We show that multi-dimensional basis functions are constructed as tensor products of one-dimensional basis functions and discuss the treatment of polynomial and trigonometric nonlinearities. Parametric uncertainties are modeled by finite-support probability densities. Stochastic forcings are discretized using truncated Karhunen-Loeve expansions. The companion paper 'Modeling Multibody Dynamic Systems With Uncertainties. Part II: Numerical Applications' illustrates the use of the proposed methodology on a selected set of test problems. The overall conclusion is that despite its limitations, polynomial chaos is a powerful approach for the simulation of multibody systems with uncertainties
The relationship between cost system complexity, purposes of use, and cost system effectiveness
Schoute, M.
2009-01-01
This paper uses survey data from 133 Dutch, medium-sized manufacturing firms to examine the associations between cost system complexity (in terms of the applied overhead absorption procedures), purposes of use, and cost system effectiveness. First, factor analysis identifies two underlying
Implementation of a Cost-Accounting System for Visibility of Weapon Systems Life-Cycle Costs
National Research Council Canada - National Science Library
Ugone, Mary
2001-01-01
.... The DoD Acquisition Reform Goal 10 required DoD to define requirements and establish an implementation plan for a cost-accounting system that provides routine visibility into weapon system life-cycle...
International Nuclear Information System (INIS)
Weijde, Adriaan Hendrik van der; Hobbs, Benjamin F.
2012-01-01
Aggressive development of renewable electricity sources will require significant expansions in transmission infrastructure. We present a stochastic two-stage optimisation model that captures the multistage nature of transmission planning under uncertainty and use it to evaluate interregional grid reinforcements in Great Britain (GB). In our model, a proactive transmission planner makes investment decisions in two time periods, each time followed by a market response. Uncertainty is represented by economic, technology, and regulatory scenarios, and first-stage investments must be made before it is known which scenario will occur. The model allows us to identify expected cost-minimising first-stage investments, as well as estimate the value of information, the cost of ignoring uncertainty, and the value of flexibility. Our results show that ignoring risk in planning transmission for renewables has quantifiable economic consequences, and that considering uncertainty can yield decisions that have lower expected costs than traditional deterministic planning methods. In the GB case, the value of information and cost of disregarding uncertainty in transmission planning were of the same order of magnitude (approximately £100 M, in present worth terms). Further, the best plan under a risk-neutral decision criterion can differ from the best under risk-aversion. Finally, a traditional sensitivity analysis-based robustness analysis also yields different results than the stochastic model, although the former's expected cost is not much higher.
International Nuclear Information System (INIS)
Hasegawa, Keita; Komiyama, Ryoichi; Fujii, Yasumasa
2016-01-01
The paper presents an economic rationality analysis of power generation mix by stochastic dynamic programming considering fuel price uncertainties and supply disruption risks such as import disruption and nuclear power plant shutdown risk. The situation revolving around Japan's energy security adopted the past statistics, it cannot be applied to a quantitative analysis of future uncertainties. Further objective and quantitative evaluation methods are required in order to analyze Japan's energy system and make it more resilient in sight of long time scale. In this paper, the authors firstly develop the cost minimization model considering oil and natural gas price respectively by stochastic dynamic programming. Then, the authors show several premises of model and an example of result with related to crude oil stockpile, liquefied natural gas stockpile and nuclear power plant capacity. (author)
[Method for optimal sensor placement in water distribution systems with nodal demand uncertainties].
Liu, Shu-Ming; Wu, Xue; Ouyang, Le-Yan
2013-08-01
The notion of identification fitness was proposed for optimizing sensor placement in water distribution systems. Nondominated Sorting Genetic Algorithm II was used to find the Pareto front between minimum overlap of possible detection times of two events and the best probability of detection, taking nodal demand uncertainties into account. This methodology was applied to an example network. The solutions show that the probability of detection and the number of possible locations are not remarkably affected by nodal demand uncertainties, but the sources identification accuracy declines with nodal demand uncertainties.
Activity-Based Costing Systems for Higher Education.
Day, Dennis H.
1993-01-01
Examines traditional costing models utilized in higher education and pinpoints shortcomings related to proper identification of costs. Describes activity-based costing systems as a superior alternative for cost identification, measurement, and allocation. (MLF)
International Nuclear Information System (INIS)
Ngamroo, Issarachai
2010-01-01
It is well known that the superconducting magnetic energy storage (SMES) is able to quickly exchange active and reactive power with the power system. The SMES is expected to be the smart storage device for power system stabilization. Although the stabilizing effect of SMES is significant, the SMES is quite costly. Particularly, the superconducting magnetic coil size which is the essence of the SMES, must be carefully selected. On the other hand, various generation and load changes, unpredictable network structure, etc., cause system uncertainties. The power controller of SMES which is designed without considering such uncertainties, may not tolerate and loses stabilizing effect. To overcome these problems, this paper proposes the new design of robust SMES controller taking coil size and system uncertainties into account. The structure of the active and reactive power controllers is the 1st-order lead-lag compensator. No need for the exact mathematical representation, system uncertainties are modeled by the inverse input multiplicative perturbation. Without the difficulty of the trade-off of damping performance and robustness, the optimization problem of control parameters is formulated. The particle swarm optimization is used for solving the optimal parameters at each coil size automatically. Based on the normalized integral square error index and the consideration of coil current constraint, the robust SMES with the smallest coil size which still provides the satisfactory stabilizing effect, can be achieved. Simulation studies in the two-area four-machine interconnected power system show the superior robustness of the proposed robust SMES with the smallest coil size under various operating conditions over the non-robust SMES with large coil size.
Ngamroo, Issarachai
2010-12-01
It is well known that the superconducting magnetic energy storage (SMES) is able to quickly exchange active and reactive power with the power system. The SMES is expected to be the smart storage device for power system stabilization. Although the stabilizing effect of SMES is significant, the SMES is quite costly. Particularly, the superconducting magnetic coil size which is the essence of the SMES, must be carefully selected. On the other hand, various generation and load changes, unpredictable network structure, etc., cause system uncertainties. The power controller of SMES which is designed without considering such uncertainties, may not tolerate and loses stabilizing effect. To overcome these problems, this paper proposes the new design of robust SMES controller taking coil size and system uncertainties into account. The structure of the active and reactive power controllers is the 1st-order lead-lag compensator. No need for the exact mathematical representation, system uncertainties are modeled by the inverse input multiplicative perturbation. Without the difficulty of the trade-off of damping performance and robustness, the optimization problem of control parameters is formulated. The particle swarm optimization is used for solving the optimal parameters at each coil size automatically. Based on the normalized integral square error index and the consideration of coil current constraint, the robust SMES with the smallest coil size which still provides the satisfactory stabilizing effect, can be achieved. Simulation studies in the two-area four-machine interconnected power system show the superior robustness of the proposed robust SMES with the smallest coil size under various operating conditions over the non-robust SMES with large coil size.
International Nuclear Information System (INIS)
Campolina, Daniel de Almeida Magalhães
2015-01-01
There is an uncertainty for all the components that comprise the model of a nuclear system. Assessing the impact of uncertainties in the simulation of fissionable material systems is essential for a realistic calculation that has been replacing conservative model calculations as the computational power increases. The propagation of uncertainty in a simulation using a Monte Carlo code by sampling the input parameters is recent because of the huge computational effort required. By analyzing the propagated uncertainty to the effective neutron multiplication factor (k eff ), the effects of the sample size, computational uncertainty and efficiency of a random number generator to represent the distributions that characterize physical uncertainty in a light water reactor was investigated. A program entitled GB s ample was implemented to enable the application of the random sampling method, which requires an automated process and robust statistical tools. The program was based on the black box model and the MCNPX code was used in and parallel processing for the calculation of particle transport. The uncertainties considered were taken from a benchmark experiment in which the effects in k eff due to physical uncertainties is done through a conservative method. In this work a script called GB s ample was implemented to automate the sampling based method, use multiprocessing and assure the necessary robustness. It has been found the possibility of improving the efficiency of the random sampling method by selecting distributions obtained from a random number generator in order to obtain a better representation of uncertainty figures. After the convergence of the method is achieved, in order to reduce the variance of the uncertainty propagated without increase in computational time, it was found the best number o components to be sampled. It was also observed that if the sampling method is used to calculate the effect on k eff due to physical uncertainties reported by
Adaptive robust fault-tolerant control for linear MIMO systems with unmatched uncertainties
Zhang, Kangkang; Jiang, Bin; Yan, Xing-Gang; Mao, Zehui
2017-10-01
In this paper, two novel fault-tolerant control design approaches are proposed for linear MIMO systems with actuator additive faults, multiplicative faults and unmatched uncertainties. For time-varying multiplicative and additive faults, new adaptive laws and additive compensation functions are proposed. A set of conditions is developed such that the unmatched uncertainties are compensated by actuators in control. On the other hand, for unmatched uncertainties with their projection in unmatched space being not zero, based on a (vector) relative degree condition, additive functions are designed to compensate for the uncertainties from output channels in the presence of actuator faults. The developed fault-tolerant control schemes are applied to two aircraft systems to demonstrate the efficiency of the proposed approaches.
Changing World, Unchanging Accounting? Cost Systems for Hungarian Agricultural Companies
Zoltán Musinszki
2011-01-01
The literature of agricultural cost accounting has defined the definition of cost centres and cost bearers, the contents of the accounts, the procedures and methods for cost accounting and unit cost calculation without any significant changes for decades now. Do the agricultural companies set up and operate their own cost allocation and unit cost calculation systems on procedures made for state owned farms and cooperatives, or do they align their cost system with the challenges of our times? ...
Planning regional energy system in association with greenhouse gas mitigation under uncertainty
Energy Technology Data Exchange (ETDEWEB)
Li, Y.P.; Huang, G.H. [Research Academy of Energy and Environmental Studies, North China Electric Power University, Beijing 102206 (China); Chen, X. [Key Laboratory of Oasis Ecology and Desert Environment, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang 830011 (China)
2011-03-15
Greenhouse gas (GHG) concentrations are expected to continue to rise due to the ever-increasing use of fossil fuels and ever-boosting demand for energy. This leads to inevitable conflict between satisfying increasing energy demand and reducing GHG emissions. In this study, an integrated fuzzy-stochastic optimization model (IFOM) is developed for planning energy systems in association with GHG mitigation. Multiple uncertainties presented as probability distributions, fuzzy-intervals and their combinations are allowed to be incorporated within the framework of IFOM. The developed method is then applied to a case study of long-term planning of a regional energy system, where integer programming (IP) technique is introduced into the IFOM to facilitate dynamic analysis for capacity-expansion planning of energy-production facilities within a multistage context to satisfy increasing energy demand. Solutions related fuzzy and probability information are obtained and can be used for generating decision alternatives. The results can not only provide optimal energy resource/service allocation and capacity-expansion plans, but also help decision-makers identify desired policies for GHG mitigation with a cost-effective manner. (author)
Multilevel Production Systems with Dependent Demand with Uncertainty of Lead Times
Directory of Open Access Journals (Sweden)
Haibatolah Sadeghi
2016-01-01
Full Text Available This study considers a multilevel assembly system with several components in each sublevel. It is assumed that actual lead time for all components is probabilistic; and periodic order quantity (POQ policy for ordering is utilized. If at a certain level a job is not received at the expected time, a delay is incurred at the delivery of production at this level and this may result in backorders of the finished product. It is assumed in this case that a fixed percentage of the shortage is backlogged and other sales are lost. In the real situation, some but not all customers will wait for backlogged components during a period of shortage, such as for fashionable commodities or high-tech products with the short product life cycle. The objective of this study is to find the planned lead time and periodicity for the total components in order to minimize the expected fixed ordering, holding, and partial backlogging costs for the finished product. In this study, it is assumed that a percentage of components at each level are scrap. A general mathematical model is suggested and the method developed can be used for optimization planned lead time and periodicity for such an MRP system under lead time uncertainties.
Hughes, J. D.; Metz, P. A.
2014-12-01
Most watershed studies include observation-based water budget analyses to develop first-order estimates of significant flow terms. Surface-water/groundwater (SWGW) exchange is typically assumed to be equal to the residual of the sum of inflows and outflows in a watershed. These estimates of SWGW exchange, however, are highly uncertain as a result of the propagation of uncertainty inherent in the calculation or processing of the other terms of the water budget, such as stage-area-volume relations, and uncertainties associated with land-cover based evapotranspiration (ET) rate estimates. Furthermore, the uncertainty of estimated SWGW exchanges can be magnified in large wetland systems that transition from dry to wet during wet periods. Although it is well understood that observation-based estimates of SWGW exchange are uncertain it is uncommon for the uncertainty of these estimates to be directly quantified. High-level programming languages like Python can greatly reduce the effort required to (1) quantify the uncertainty of estimated SWGW exchange in large wetland systems and (2) evaluate how different approaches for partitioning land-cover data in a watershed may affect the water-budget uncertainty. We have used Python with the Numpy, Scipy.stats, and pyDOE packages to implement an unconstrained Monte Carlo approach with Latin Hypercube sampling to quantify the uncertainty of monthly estimates of SWGW exchange in the Floral City watershed of the Tsala Apopka wetland system in west-central Florida, USA. Possible sources of uncertainty in the water budget analysis include rainfall, ET, canal discharge, and land/bathymetric surface elevations. Each of these input variables was assigned a probability distribution based on observation error or spanning the range of probable values. The Monte Carlo integration process exposes the uncertainties in land-cover based ET rate estimates as the dominant contributor to the uncertainty in SWGW exchange estimates. We will discuss
Reliability/Cost Evaluation on Power System connected with Wind Power for the Reserve Estimation
DEFF Research Database (Denmark)
Lee, Go-Eun; Cha, Seung-Tae; Shin, Je-Seok
2012-01-01
Wind power is ideally a renewable energy with no fuel cost, but has a risk to reduce reliability of the whole system because of uncertainty of the output. If the reserve of the system is increased, the reliability of the system may be improved. However, the cost would be increased. Therefore...... the reserve needs to be estimated considering the trade-off between reliability and economic aspects. This paper suggests a methodology to estimate the appropriate reserve, when wind power is connected to the power system. As a case study, when wind power is connected to power system of Korea, the effects...
Estimation of Uncertainty in Aerosol Concentration Measured by Aerosol Sampling System
Energy Technology Data Exchange (ETDEWEB)
Lee, Jong Chan; Song, Yong Jae; Jung, Woo Young; Lee, Hyun Chul; Kim, Gyu Tae; Lee, Doo Yong [FNC Technology Co., Yongin (Korea, Republic of)
2016-10-15
FNC Technology Co., Ltd has been developed test facilities for the aerosol generation, mixing, sampling and measurement under high pressure and high temperature conditions. The aerosol generation system is connected to the aerosol mixing system which injects SiO{sub 2}/ethanol mixture. In the sampling system, glass fiber membrane filter has been used to measure average mass concentration. Based on the experimental results using main carrier gas of steam and air mixture, the uncertainty estimation of the sampled aerosol concentration was performed by applying Gaussian error propagation law. FNC Technology Co., Ltd. has been developed the experimental facilities for the aerosol measurement under high pressure and high temperature. The purpose of the tests is to develop commercial test module for aerosol generation, mixing and sampling system applicable to environmental industry and safety related system in nuclear power plant. For the uncertainty calculation of aerosol concentration, the value of the sampled aerosol concentration is not measured directly, but must be calculated from other quantities. The uncertainty of the sampled aerosol concentration is a function of flow rates of air and steam, sampled mass, sampling time, condensed steam mass and its absolute errors. These variables propagate to the combination of variables in the function. Using operating parameters and its single errors from the aerosol test cases performed at FNC, the uncertainty of aerosol concentration evaluated by Gaussian error propagation law is less than 1%. The results of uncertainty estimation in the aerosol sampling system will be utilized for the system performance data.
Evaluation of Uniform Cost Accounting System to Fully Capture Depot Level Repair Costs.
1985-12-01
RD-RI65 522 EVALUATION OF UNIFORM COST ACCOUNTING SYSTEM TO FULLY i/I CAPTURE DEPOT LEVEL REPAIR COSTS (U) NAVAL POSTGRADUATE SCHOOL MONTEREY CA D R...8217.LECTE B ,- THESIS EVALUATION OF UNIFORM COST ACCOUNTING SYSTEM 0TO FULLY CAPTURE DEPOT LEVEL REPAIR COSTS Jby __jDavid Richmond O’Brien lj,,, December...Include Security Classification) EVALUATION OF UNIFORM COST ACCOUNTING SYSTEM TO FULLY CAPTURE DEPOT LEVEL REPAIR COSTS 12 PERSONAL AUTHOR(S) O’Brien- David
van der Schaft, Arjan
1995-01-01
The approach to robust stabilization of linear systems using normalized left coprime factorizations with H∞ bounded uncertainty is generalized to nonlinear systems. A nonlinear perturbation model is derived, based on the concept of a stable kernel representation of nonlinear systems. The robust
The wave function and minimum uncertainty function of the bound quadratic Hamiltonian system
Yeon, Kyu Hwang; Um, Chung IN; George, T. F.
1994-01-01
The bound quadratic Hamiltonian system is analyzed explicitly on the basis of quantum mechanics. We have derived the invariant quantity with an auxiliary equation as the classical equation of motion. With the use of this invariant it can be determined whether or not the system is bound. In bound system we have evaluated the exact eigenfunction and minimum uncertainty function through unitary transformation.
Uwizeye, U.A.; Groen, E.A.; Gerber, P.J.; Schulte, Rogier P.O.; Boer, de I.J.M.
2016-01-01
The study aims to illustrate a method to identify important input parameters that explain most of the output variance ofenvironmental assessment models. The method is tested for the computation of life-cycle nitrogen (N) use efficiencyindicators among mixed dairy production systems in Rwanda. We
MODELLING OF UNCERTAINTY IN MINIMISING THE COST OF INVENTORY FOR DISASTER RELIEF
Directory of Open Access Journals (Sweden)
E. Van Wyk
2012-01-01
Full Text Available ENGLISH ABSTRACT: Natural disasters – and even those caused by people – are largely unpredictable. So disasters need to be researched and their impact fully understood, so that the aid supplies required to ensure survival during and after disaster events will be available. The member states of the Southern African Development Community (SADC are the countries of interest for this paper, as insufficient research has been conducted into inventory pre-positioning for disaster response in these countries. It is vital to anticipate the needs of disaster victims in potential disasters. These needs are evaluated according to the types and amounts of aid supplies required. This paper proposes a stochastic inventory model that can be applied in a generic way to any SADC country, providing a means to improve disaster preparedness through keeping aid supplies in pre-positioned facilities in the SADC region, at reasonable and affordable cost.
AFRIKAANSE OPSOMMING: Natuurlike en mensgemaakte rampe is grootliks onvoorspelbaar. Gevolglik moet rampe nagevors en hul impak ten volle begryp word, sodat noodvoorrade wat benodig word vir oorlewing doeltreffend beplan kan word vir aanwending tydens en na rampgebeure. Die lede van die Suid-Afrikaanse Ontwikkelingsgemeenskap (SAOG is die lande van belang vir hierdie artikel omrede navorsing oor voorraadhouding vir rampreaksie in hierdie betrokke lande tot nog toe onvoldoende was. Dit is noodsaaklik om doeltreffend in die behoeftes van rampslagoffers te voorsien. Hierdie behoeftes word beoordeel na aanleiding van die aard en hoeveelhede van noodvoorrade wat benodig mag word in ramptoestande. Hierdie artikel stel ’n stochastiese voorraadmodel voor vir toepassing op ’n generiese wyse in enige SAOG land, om sodoende ’n metode te verskaf om rampvoorbereiding te verbeter deur die opgaar van noodvoorrade in vooraf-geïdentifiseerde fasiliteite binne die SAOG, teen redelike en bekostigbare koste.
Uncertainties in different level assessments of domestic ventilation systems
Bokel, R.M.J.; Yang, Z.; Cauberg, J.J.M.
2013-01-01
In order to improve the quality of ventilation systems, assessments are widely used. In this paper, 3 main assessment levels are distinguished based on the number of ventilation systems to be assessed and the assessment objective. The main assessment levels distinguished in this paper are global
Energy Technology Data Exchange (ETDEWEB)
Turinsky, Paul J [North Carolina State Univ., Raleigh, NC (United States); Abdel-Khalik, Hany S [North Carolina State Univ., Raleigh, NC (United States); Stover, Tracy E [North Carolina State Univ., Raleigh, NC (United States)
2011-03-01
An optimization technique has been developed to select optimized experimental design specifications to produce data specifically designed to be assimilated to optimize a given reactor concept. Data from the optimized experiment is assimilated to generate posteriori uncertainties on the reactor concept’s core attributes from which the design responses are computed. The reactor concept is then optimized with the new data to realize cost savings by reducing margin. The optimization problem iterates until an optimal experiment is found to maximize the savings. A new generation of innovative nuclear reactor designs, in particular fast neutron spectrum recycle reactors, are being considered for the application of closing the nuclear fuel cycle in the future. Safe and economical design of these reactors will require uncertainty reduction in basic nuclear data which are input to the reactor design. These data uncertainty propagate to design responses which in turn require the reactor designer to incorporate additional safety margin into the design, which often increases the cost of the reactor. Therefore basic nuclear data needs to be improved and this is accomplished through experimentation. Considering the high cost of nuclear experiments, it is desired to have an optimized experiment which will provide the data needed for uncertainty reduction such that a reactor design concept can meet its target accuracies or to allow savings to be realized by reducing the margin required due to uncertainty propagated from basic nuclear data. However, this optimization is coupled to the reactor design itself because with improved data the reactor concept can be re-optimized itself. It is thus desired to find the experiment that gives the best optimized reactor design. Methods are first established to model both the reactor concept and the experiment and to efficiently propagate the basic nuclear data uncertainty through these models to outputs. The representativity of the experiment
Uncertainty analysis methods for estimation of reliability of passive system of VHTR
International Nuclear Information System (INIS)
Han, S.J.
2012-01-01
An estimation of reliability of passive system for the probabilistic safety assessment (PSA) of a very high temperature reactor (VHTR) is under development in Korea. The essential approach of this estimation is to measure the uncertainty of the system performance under a specific accident condition. The uncertainty propagation approach according to the simulation of phenomenological models (computer codes) is adopted as a typical method to estimate the uncertainty for this purpose. This presentation introduced the uncertainty propagation and discussed the related issues focusing on the propagation object and its surrogates. To achieve a sufficient level of depth of uncertainty results, the applicability of the propagation should be carefully reviewed. For an example study, Latin-hypercube sampling (LHS) method as a direct propagation was tested for a specific accident sequence of VHTR. The reactor cavity cooling system (RCCS) developed by KAERI was considered for this example study. This is an air-cooled type passive system that has no active components for its operation. The accident sequence is a low pressure conduction cooling (LPCC) accident that is considered as a design basis accident for the safety design of VHTR. This sequence is due to a large failure of the pressure boundary of the reactor system such as a guillotine break of coolant pipe lines. The presentation discussed the obtained insights (benefit and weakness) to apply an estimation of reliability of passive system
A Modern Costing System: Activity Based Costing and An Application On A Textile Company
Titiz, İsmet; Altunay, Mehmet Akif
2012-01-01
The aim of this study is understanding Activity Based Costing which is one of the systems of modern cost approaches. Main concepts about activity based costing is defined and development of the system is identified. In the last part, an application about the activity based costing system in a textile company is explained and the results are analyzed.
PLACE OF PRODUCTION COSTS SYSTEM ANALYSIS IN SYSTEM ANALYSIS
Directory of Open Access Journals (Sweden)
Mariia CHEREDNYCHENKO
2016-12-01
Full Text Available Current economic conditions require the development and implementation of an adequate system of production costs, which would ensure a steady profit growth and production volumes in a highly competitive, constantly increasing input prices and tariffs. This management system must be based on an integrated production costs system analysis (PCSA, which would provide all operating costs management subsystems necessary information to design and make better management decisions. It provides a systematic analysis of more opportunities in knowledge, creating conditions of integrity mechanism knowledge object consisting of elements that show intersystem connections, each of which has its own defined and limited objectives, relationship with the environment.
System cuts radwaste-disposal cost
International Nuclear Information System (INIS)
May, J.R.
1978-01-01
Pilot-plant and full-scale prototype-system test data on a new volume-reduction system for low-level radioactive wastes, of the type generated by nuclear plants, indicate that total present costs for radwaste disposal can be reduced by more than 50%. In 1975, Newport News Industrial Corp. and Energy Inc. decided to develop cooperatively a fluidized-bed process that would combine the features of a calciner and an incinerator. The new radwaste-volume-reduction system, designated RWR-1, can reduce the volume of concentrated liquids, ion-exchange resin beads, filter sludges, and various combustible solids, such as protective clothing, rags, paper, wood, and plastics
Uncertainty analysis for the BEACON-COLSS core monitoring system application
International Nuclear Information System (INIS)
Morita, T.; Boyd, W.A.; Seong, K.B.
2005-01-01
This paper will cover the measurement uncertainty analysis of BEACON-COLSS core monitoring system. The uncertainty evaluation is made by using a BEACON-COLSS simulation program. By simulating the BEACON on-line operation for analytically generated reactor conditions, accuracy of the 'Measured' results can be evaluated by comparing to analytically generated 'Truth'. The DNB power margin is evaluated based on the Combustion Engineering's Modified Statistical Combination of Uncertainties (MSCU) using the CETOPD code for the DNBR calculation. A BEACON-COLSS simulation program for the uncertainty evaluation function has been established for plant applications. Qualification work has been completed for two Combustion Engineering plants. Results of the BEACON-COLSS measured peaking factors and DNBR power margin are plant type dependent and are applicable to reload cores as long as the core geometry and detector layout are unchanged. (authors)
Park, DaeKil
2018-06-01
The dynamics of entanglement and uncertainty relation is explored by solving the time-dependent Schrödinger equation for coupled harmonic oscillator system analytically when the angular frequencies and coupling constant are arbitrarily time dependent. We derive the spectral and Schmidt decompositions for vacuum solution. Using the decompositions, we derive the analytical expressions for von Neumann and Rényi entropies. Making use of Wigner distribution function defined in phase space, we derive the time dependence of position-momentum uncertainty relations. To show the dynamics of entanglement and uncertainty relation graphically, we introduce two toy models and one realistic quenched model. While the dynamics can be conjectured by simple consideration in the toy models, the dynamics in the realistic quenched model is somewhat different from that in the toy models. In particular, the dynamics of entanglement exhibits similar pattern to dynamics of uncertainty parameter in the realistic quenched model.
Calculation of the uncertainty of HP (10) evaluation for a thermoluminescent dosimetry system
International Nuclear Information System (INIS)
Ferreira, M.S.; Silva, E.R.; Mauricio, C.L.P.
2016-01-01
Full interpretation of dose assessment only can be performed when the uncertainty of the measurement is known. The aim of this study is to calculate the uncertainty of the TL dosimetry system of the LDF/IRD for evaluation of H P (10) for photons. It has been done by experimental measurements, extraction of information from documents and calculation of uncertainties based on ISO GUM. Energy and angular dependence is the most important source to the combined u c (y) and expanded (U) uncertainty. For 10 mSv, it was obtained u c (y) = 1,99 mSv and U = 3,98 mSv for 95% of coverage interval. (author)
Monte Carlo approaches for uncertainty quantification of criticality for system dimensions
International Nuclear Information System (INIS)
Kiedrowski, B.C.; Brown, F.B.
2013-01-01
One of the current challenges in nuclear engineering computations is the issue of performing uncertainty analysis for either calculations or experimental measurements. This paper specifically focuses on the issue of estimating the uncertainties arising from geometric tolerances. For this paper, two techniques for uncertainty quantification are studied. The first is the forward propagation technique, which can be thought of as a 'brute force' approach; uncertain system parameters are randomly sampled, the calculation is run, and uncertainties are found from the empirically obtained distribution of results. This approach need make no approximations in principle, but is very computationally expensive. The other approach investigated is the adjoint-based approach; system sensitivities are computed via a single Monte Carlo calculation and those are used with a covariance matrix to provide a linear estimate of the uncertainty. Demonstration calculations are performed with the MCNP6 code for both techniques. The 2 techniques are tested on 2 cases: the first case is a solid, bare cylinder of Pu-metal while the second case is a can of plutonium nitrate solution. The results show that the forward and adjoint approaches appear to agree in some cases where the responses are not non-linearly correlated. In other cases, the uncertainties in the effective multiplication k disagree for reasons not yet known
Yang, Jun; Zolotas, Argyrios; Chen, Wen-Hua; Michail, Konstantinos; Li, Shihua
2011-07-01
Robust control of a class of uncertain systems that have disturbances and uncertainties not satisfying "matching" condition is investigated in this paper via a disturbance observer based control (DOBC) approach. In the context of this paper, "matched" disturbances/uncertainties stand for the disturbances/uncertainties entering the system through the same channels as control inputs. By properly designing a disturbance compensation gain, a novel composite controller is proposed to counteract the "mismatched" lumped disturbances from the output channels. The proposed method significantly extends the applicability of the DOBC methods. Rigorous stability analysis of the closed-loop system with the proposed method is established under mild assumptions. The proposed method is applied to a nonlinear MAGnetic LEViation (MAGLEV) suspension system. Simulation shows that compared to the widely used integral control method, the proposed method provides significantly improved disturbance rejection and robustness against load variation. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Kim, Myung Hyeon; Shin, Myeong Won; Rhy, Seok Jin; Cho, Dong Keon; Park, Dong Hwan [Kyunghee Univ., Seoul (Korea, Republic of); Cheong, Beom Jin [Minstry of Science and Technology, Gwacheon (Korea, Republic of)
1998-03-15
The main objective os to develop a technical standards for the facility operation of the interm, spent fuel storage facility and to develop a draft for the technical criteria to be legislated. The another objective os to define a uncertainty evaluation system for burn up credit application in criticality analysis and to investigate an applicability of this topic for future regulatory activity. Investigate a status of art for the operational criteria of spent fuel interm wet storage. Collect relevant laws, decree, notices and standards related to the operation of storage facility and study on the legislation system. Develop a draft of technical standards and criteria to be legislated. Define an evaluation system for the uncertainty analysis and study on the status of art in the field of criticality safety analysis. Develop an uncertainty evaluation system in criticality analysis with burnup credit and investigate an applicability as well as its benefits of this policy.
Linear systems with unstructured multiplicative uncertainty: Modeling and robust stability analysis.
Directory of Open Access Journals (Sweden)
Radek Matušů
Full Text Available This article deals with continuous-time Linear Time-Invariant (LTI Single-Input Single-Output (SISO systems affected by unstructured multiplicative uncertainty. More specifically, its aim is to present an approach to the construction of uncertain models based on the appropriate selection of a nominal system and a weight function and to apply the fundamentals of robust stability investigation for considered sort of systems. The initial theoretical parts are followed by three extensive illustrative examples in which the first order time-delay, second order and third order plants with parametric uncertainty are modeled as systems with unstructured multiplicative uncertainty and subsequently, the robust stability of selected feedback loops containing constructed models and chosen controllers is analyzed and obtained results are discussed.
Liu, Lei; Wang, Zhanshan; Zhang, Huaguang
2018-04-01
This paper is concerned with the robust optimal tracking control strategy for a class of nonlinear multi-input multi-output discrete-time systems with unknown uncertainty via adaptive critic design (ACD) scheme. The main purpose is to establish an adaptive actor-critic control method, so that the cost function in the procedure of dealing with uncertainty is minimum and the closed-loop system is stable. Based on the neural network approximator, an action network is applied to generate the optimal control signal and a critic network is used to approximate the cost function, respectively. In contrast to the previous methods, the main features of this paper are: 1) the ACD scheme is integrated into the controllers to cope with the uncertainty and 2) a novel cost function, which is not in quadric form, is proposed so that the total cost in the design procedure is reduced. It is proved that the optimal control signals and the tracking errors are uniformly ultimately bounded even when the uncertainty exists. Finally, a numerical simulation is developed to show the effectiveness of the present approach.
Role Of Environment Uncertainty On Management Information System-Literature Approach
Directory of Open Access Journals (Sweden)
Christine Dwi Karya Susilawati
2015-08-01
Full Text Available The purpose of this research is to find role of environmental uncertainty on the quality of management information system with the literature review. Environmental uncertainty is the inability of the individual to capture the environmental factors from outside the company who are not sure which affect the companies that will impact on the quality of management information system application when it lowered the individuals inability to capture the environmental factors from outside uncertain it will improve the quality of management information system application.
International Nuclear Information System (INIS)
Fu, D.Z.; Zheng, Z.Y.; Shi, H.B.; Xiao, Rui; Huang, G.H.; Li, Y.P.
2017-01-01
In this study, an interval two-stage double-stochastic single-sided fuzzy chance-constrained programming model is developed for supporting fuel management of a community-level district heating system (DHS) fed with both traditional fossil fuels and renewable biofuels under multiple uncertainties. The proposed model is based on the integration of interval parameter programming and single-sided fuzzy chance-constrained programming within an improved stochastic programming framework to tackle the uncertainties expressed as crisp intervals, fuzzy relationship, and probability distributions. Through transforming and solving the model, the related fuzzy and stochastic information can be effectively reflected in the generated solutions. A real fuel management case of a DHS located in Junpu New District of Dalian is utilized to demonstrate the model applicability. The obtained solutions provides an effective linkage in terms of both ‘‘quality’’ and ‘‘quantity’’ aspects for fuel management under various scenarios associated with multiple factors, and thus can help the decision makers to identify desired fuel allotment patterns. Moreover, this study is also useful for decision makers to address the other challenges (e.g. the imbalance between fuel supply and demand, the contradiction between air-pollution emission and environmental protection, as well as the tradeoff between the total heating cost and system satisfaction degree) generated in the fuel management processes. - Highlights: • A feasible two-stage stochastic programming method is improved. • A multi-fuel management model is developed under multiple uncertainties. • The fuel supply pattern for a district heating system can be obtained. • The variation tendencies of the pollutant emissions are examined. • Tradeoff analyses between system satisfaction degree and cost are carried out.
A robust active control system for shimmy damping in the presence of free play and uncertainties
Orlando, Calogero; Alaimo, Andrea
2017-02-01
Shimmy vibration is the oscillatory motion of the fork-wheel assembly about the steering axis. It represents one of the major problem of aircraft landing gear because it can lead to excessive wear, discomfort as well as safety concerns. Based on the nonlinear model of the mechanics of a single wheel nose landing gear (NLG), electromechanical actuator and tire elasticity, a robust active controller capable of damping shimmy vibration is designed and investigated in this study. A novel Decline Population Swarm Optimization (PDSO) procedure is introduced and used to select the optimal parameters for the controller. The PDSO procedure is based on a decline demographic model and shows high global search capability with reduced computational costs. The open and closed loop system behavior is analyzed under different case studies of aeronautical interest and the effects of torsional free play on the nose landing gear response are also studied. Plant parameters probabilistic uncertainties are then taken into account to assess the active controller robustness using a stochastic approach.
Internal design of technical systems under conditions of uncertainty
Energy Technology Data Exchange (ETDEWEB)
Krasnoshchekov, P S; Morozov, V V; Fedorov, V V
1982-03-01
An investigation is made of a model of internal design of a complex technical system in the presence of uncertain factors. The influence of an opponent on the design is examined. The concepts of hierarchical and balanced compatibility between the criteria of the designer, the opponent and the segregations functions are introduced and studied. The connection between the approach proposed and the methods of artificial intelligence is discussed. 5 references.
Development of an EVA systems cost model. Volume 3: EVA systems cost model
1975-01-01
The EVA systems cost model presented is based on proposed EVA equipment for the space shuttle program. General information on EVA crewman requirements in a weightless environment and an EVA capabilities overview are provided.
International Nuclear Information System (INIS)
2008-01-01
System planners face today unique challenges to accommodate the new uncertainties in markets, loads and generation and to develop system plans that balance reliability, economy and risk. The report summarizes a survey of the methods used worldwide. In addition, case examples are provided to illustrate in more detail these methods
International Nuclear Information System (INIS)
Sharma, Vivek; Sharma, B.B.; Nath, R.
2017-01-01
In the present manuscript, observer based synchronization and message recovery scheme is discussed for a system with uncertainties. LMI conditions are analytically derived solution of which gives the observer design matrices. Earlier approaches have used adaptive laws to address the uncertainties, however in present work, decoupling approach is used to make observer robust against uncertainties. The methodology requires upper bounds on nonlinearity and the message signal and estimates for these bounds are generated adaptively. Thus no information about the nature of nonlinearity and associated Lipschitz constant is needed in proposed approach. Message signal is recovered using equivalent output injection which is a low pass filtered equivalent of the discontinuous effort required to maintain the sliding motion. Finally, the efficacy of proposed Nonlinear Unknown Input Sliding Mode Observer (NUISMO) for chaotic communication is verified by conducting simulation studies on two chaotic systems i.e. third order Chua circuit and Rossler system.
Plug and Play Robust Distributed Control with Ellipsoidal Parametric Uncertainty System
Directory of Open Access Journals (Sweden)
Hong Wang-jian
2016-01-01
Full Text Available We consider a continuous linear time invariant system with ellipsoidal parametric uncertainty structured into subsystems. Since the design of a local controller uses only information on a subsystem and its neighbours, we combine the plug and play idea and robust distributed control to propose one distributed control strategy for linear system with ellipsoidal parametric uncertainty. Firstly for linear system with ellipsoidal parametric uncertainty, a necessary and sufficient condition for robust state feedback control is proposed by means of linear matrix inequality. If this necessary and sufficient condition is satisfied, this robust state feedback gain matrix can be easily derived to guarantee robust stability and prescribed closed loop performance. Secondly the plug and play idea is introduced in the design process. Finally by one example of aircraft flutter model parameter identification, the efficiency of the proposed control strategy can be easily realized.
DEFF Research Database (Denmark)
Abdul Samad, Noor Asma Fazli Bin; Sin, Gürkan; Gernaey, Krist
2013-01-01
This paper presents the application of uncertainty and sensitivity analysis as part of a systematic modelbased process monitoring and control (PAT) system design framework for crystallization processes. For the uncertainty analysis, the Monte Carlo procedure is used to propagate input uncertainty...
Evaluation of the uncertainty in an EBT3 film dosimetry system utilizing net optical density.
Marroquin, Elsa Y León; Herrera González, José A; Camacho López, Miguel A; Barajas, José E Villarreal; García-Garduño, Olivia A
2016-09-08
Radiochromic film has become an important tool to verify dose distributions for intensity-modulated radiotherapy (IMRT) and quality assurance (QA) procedures. A new radiochromic film model, EBT3, has recently become available, whose composition and thickness of the sensitive layer are the same as those of previous EBT2 films. However, a matte polyester layer was added to EBT3 to prevent the formation of Newton's rings. Furthermore, the symmetrical design of EBT3 allows the user to eliminate side-orientation dependence. This film and the flatbed scanner, Epson Perfection V750, form a dosimetry system whose intrinsic characteristics were studied in this work. In addition, uncertainties associated with these intrinsic characteristics and the total uncertainty of the dosimetry system were determined. The analysis of the response of the radiochromic film (net optical density) and the fitting of the experimental data to a potential function yielded an uncertainty of 2.6%, 4.3%, and 4.1% for the red, green, and blue channels, respectively. In this work, the dosimetry system presents an uncertainty in resolving the dose of 1.8% for doses greater than 0.8 Gy and less than 6 Gy for red channel. The films irradiated between 0 and 120 Gy show differences in the response when scanned in portrait or landscape mode; less uncertainty was found when using the portrait mode. The response of the film depended on the position on the bed of the scanner, contributing an uncertainty of 2% for the red, 3% for the green, and 4.5% for the blue when placing the film around the center of the bed of scanner. Furthermore, the uniformity and reproducibility radiochromic film and reproducibility of the response of the scanner contribute less than 1% to the overall uncertainty in dose. Finally, the total dose uncertainty was 3.2%, 4.9%, and 5.2% for red, green, and blue channels, respectively. The above uncertainty values were obtained by mini-mizing the contribution to the total dose uncertainty
Evaluation of the uncertainty in an EBT3 film dosimetry system utilizing net optical density
Marroquin, Elsa Y. León; Herrera González, José A.; Camacho López, Miguel A.; Barajas, José E. Villarreal
2016-01-01
Radiochromic film has become an important tool to verify dose distributions for intensity‐modulated radiotherapy (IMRT) and quality assurance (QA) procedures. A new radiochromic film model, EBT3, has recently become available, whose composition and thickness of the sensitive layer are the same as those of previous EBT2 films. However, a matte polyester layer was added to EBT3 to prevent the formation of Newton's rings. Furthermore, the symmetrical design of EBT3 allows the user to eliminate side‐orientation dependence. This film and the flatbed scanner, Epson Perfection V750, form a dosimetry system whose intrinsic characteristics were studied in this work. In addition, uncertainties associated with these intrinsic characteristics and the total uncertainty of the dosimetry system were determined. The analysis of the response of the radiochromic film (net optical density) and the fitting of the experimental data to a potential function yielded an uncertainty of 2.6%, 4.3%, and 4.1% for the red, green, and blue channels, respectively. In this work, the dosimetry system presents an uncertainty in resolving the dose of 1.8% for doses greater than 0.8 Gy and less than 6 Gy for red channel. The films irradiated between 0 and 120 Gy show differences in the response when scanned in portrait or landscape mode; less uncertainty was found when using the portrait mode. The response of the film depended on the position on the bed of the scanner, contributing an uncertainty of 2% for the red, 3% for the green, and 4.5% for the blue when placing the film around the center of the bed of scanner. Furthermore, the uniformity and reproducibility radiochromic film and reproducibility of the response of the scanner contribute less than 1% to the overall uncertainty in dose. Finally, the total dose uncertainty was 3.2%, 4.9%, and 5.2% for red, green, and blue channels, respectively. The above uncertainty values were obtained by minimizing the contribution to the total dose
Directory of Open Access Journals (Sweden)
Pamela Berry
2017-03-01
Full Text Available Regions dependent on agricultural production are concerned about the uncertainty associated with climate change. Extreme drought and flooding events are predicted to occur with greater frequency, requiring mitigation strategies to reduce their negative impacts. Multi-purpose local farm water retention systems can reduce water stress during drought periods by supporting irrigation. The retention systems’ capture of excess spring runoff and extreme rainfall events also reduces flood potential downstream. Retention systems may also be used for biomass production and nutrient retention. A sub-watershed scale retention system was analysed using a dynamic simulation model to predict the economic advantages in the future. Irrigated crops using water from the downstream reservoir at Pelly’s Lake, Manitoba, Canada, experienced a net decrease in gross margin in the future due to the associated irrigation and reservoir infrastructure costs. However, the multi-purpose benefits of the retention system at Pelly’s Lake of avoided flood damages, nutrient retention, carbon sequestration, and biomass production provide an economic benefit of $25,507.00/hectare of retention system/year. Multi-purpose retention systems under future climate uncertainty provide economic and environmental gains when used to avoid flood damages, for nutrient retention and carbon sequestration, and biomass production. The revenue gained from these functions can support farmers willing to invest in irrigation while providing economic and environmental benefits to the region.
Reliability analysis of water distribution systems under uncertainty
International Nuclear Information System (INIS)
Kansal, M.L.; Kumar, Arun; Sharma, P.B.
1995-01-01
In most of the developing countries, the Water Distribution Networks (WDN) are of intermittent type because of the shortage of safe drinking water. Failure of a pipeline(s) in such cases will cause not only the fall in one or more nodal heads but also the poor connectivity of source with various demand nodes of the system. Most of the previous works have used the two-step algorithm based on pathset or cutset approach for connectivity analysis. The computations become more cumbersome when connectivity of all demand nodes taken together with that of supply is carried out. In the present paper, network connectivity based on the concept of Appended Spanning Tree (AST) is suggested to compute global network connectivity which is defined as the probability of the source node being connected with all the demand nodes simultaneously. The concept of AST has distinct advantages as it attacks the problem directly rather than in an indirect way as most of the studies so far have done. Since the water distribution system is a repairable one, a general expression for pipeline avialability using the failure/repair rate is considered. Furthermore, the sensitivity of global reliability estimates due to the likely error in the estimation of failure/repair rates of various pipelines is also studied
A low-cost EDXRF analysis system
International Nuclear Information System (INIS)
Kahdeman, J.E.; Watson, W.
1984-01-01
The article deals with an EDXRF (Energy Dispersive X-ray Fluorescence) system, the Spectrace (sup TM) 4020 (Tractor X-ray). The Spectra analysis software is both powerful and flexible enough to handle a wide variety of applications. The instrument was designed to be economical by integrating the major system components into a single unit. This practical approach to hardware has cut the cost per unit. The software structure of the Spectra 4020 is presented in a flow chart. The article also contains a diagram of the hardware configuration of the instrument
International Nuclear Information System (INIS)
Sig Drellack, Lance Prothro
2007-01-01
The Underground Test Area (UGTA) Project of the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office is in the process of assessing and developing regulatory decision options based on modeling predictions of contaminant transport from underground testing of nuclear weapons at the Nevada Test Site (NTS). The UGTA Project is attempting to develop an effective modeling strategy that addresses and quantifies multiple components of uncertainty including natural variability, parameter uncertainty, conceptual/model uncertainty, and decision uncertainty in translating model results into regulatory requirements. The modeling task presents multiple unique challenges to the hydrological sciences as a result of the complex fractured and faulted hydrostratigraphy, the distributed locations of sources, the suite of reactive and non-reactive radionuclides, and uncertainty in conceptual models. Characterization of the hydrogeologic system is difficult and expensive because of deep groundwater in the arid desert setting and the large spatial setting of the NTS. Therefore, conceptual model uncertainty is partially addressed through the development of multiple alternative conceptual models of the hydrostratigraphic framework and multiple alternative models of recharge and discharge. Uncertainty in boundary conditions is assessed through development of alternative groundwater fluxes through multiple simulations using the regional groundwater flow model. Calibration of alternative models to heads and measured or inferred fluxes has not proven to provide clear measures of model quality. Therefore, model screening by comparison to independently-derived natural geochemical mixing targets through cluster analysis has also been invoked to evaluate differences between alternative conceptual models. Advancing multiple alternative flow models, sensitivity of transport predictions to parameter uncertainty is assessed through Monte Carlo simulations. The
International Nuclear Information System (INIS)
Lecocq, F.
2000-07-01
Because of the inertia of the climate system, policy makers cannot avoid making early decisions regarding climate change in a sea of uncertainties. In this context, the very legitimacy of economic analysis to tackle such questions, and in particular the underlying equity issues (who pays for climate mitigation? when?) faces widespread skepticism. This thesis aims at demonstrating how public economy still remains a powerful tool to try and put some rationale into the debate, by checking the internal consistency of the different discourses, and by providing robust insights, if not definitive answers, into climate decisions. We use a set of compact integrated climate policy optimization models to progressively introduce, articulate, and assess numerically the prominent issues at stake. We obtain three main results. We first demonstrate that the so-called timing debate between short term and long term action cannot be reduced to a mere dispute over discount rate. Given the high uncertainties surrounding climate change indeed, the margins of freedom we pass on to future generations, and in particular the technical and institutional systems we transmit, become more important than the discount rate value. Secondly, we apply the various emission quota allocation rules proposed in the literature for the enlargement of annex B to developing economies. We show that the distributive outcome of these rules depends critically on ex ante assumptions about future economic and emission growth. Therefrom, we conclude that a careful design of the institutions surrounding the tradable permits market is a necessary condition to enhance the systems robustness. Last, on a broader perspective, this thesis illustrates the complementarity between ethics and economics: though the economist does not have per se a superior word about what is fair, his toolbox is powerful enough to show how some intuitively appealing ideas, such as a zero discount rate to take care of both present and future
Uncertainty modeling in vibration, control and fuzzy analysis of structural systems
Halder, Achintya; Ayyub, Bilal M
1997-01-01
This book gives an overview of the current state of uncertainty modeling in vibration, control, and fuzzy analysis of structural and mechanical systems. It is a coherent compendium written by leading experts and offers the reader a sampling of exciting research areas in several fast-growing branches in this field. Uncertainty modeling and analysis are becoming an integral part of system definition and modeling in many fields. The book consists of ten chapters that report the work of researchers, scientists and engineers on theoretical developments and diversified applications in engineering sy
A complete low cost radon detection system
International Nuclear Information System (INIS)
Bayrak, A.; Barlas, E.; Emirhan, E.; Kutlu, Ç.; Ozben, C.S.
2013-01-01
Monitoring the 222 Rn activity through the 1200 km long Northern Anatolian fault line, for the purpose of earthquake precursory, requires large number of cost effective radon detectors. We have designed, produced and successfully tested a low cost radon detection system (a radon monitor). In the detector circuit of this monitor, First Sensor PS100-7-CER-2 windowless PIN photodiode and a custom made transempedence/shaping amplifier were used. In order to collect the naturally ionized radon progeny to the surface of the PIN photodiode, a potential of 3500 V was applied between the conductive hemi-spherical shell and the PIN photodiode. In addition to the count rate of the radon progeny, absolute pressure, humidity and temperature were logged during the measurements. A GSM modem was integrated to the system for transferring the measurements from the remote locations to the data process center. - Author-Highlights: • Low cost radon detection. • Integrated GSM modem for early warning of radon anomalies. • Radon detection in environment
Cost reduction in deep water production systems
International Nuclear Information System (INIS)
Beltrao, R.L.C.
1995-01-01
This paper describes a cost reduction program that Petrobras has conceived for its deep water field. Beginning with the Floating Production Unit, a new concept of FPSO was established where a simple system, designed to long term testing, can be upgraded, on the location, to be the definitive production unit. Regarding to the subsea system, the following projects will be considered. (1) Subsea Manifold: There are two 8-well-diverless manifolds designed for 1,000 meters presently under construction and after a value analysis, a new design was achieved for the next generation. Both projects will be discussed and a cost evaluation will also be provided. (2) Subsea Pipelines: Petrobras has just started a large program aiming to reduce cost on this important item. There are several projects such as hybrid (flexible and rigid) pipes for large diameter in deep water, alternatives laying methods, rigid riser on FPS, new material...etc. The authors intend to provide an overview of each project
Cost-effective implementation of intelligent systems
Lum, Henry, Jr.; Heer, Ewald
1990-01-01
Significant advances have occurred during the last decade in knowledge-based engineering research and knowledge-based system (KBS) demonstrations and evaluations using integrated intelligent system technologies. Performance and simulation data obtained to date in real-time operational environments suggest that cost-effective utilization of intelligent system technologies can be realized. In this paper the rationale and potential benefits for typical examples of application projects that demonstrate an increase in productivity through the use of intelligent system technologies are discussed. These demonstration projects have provided an insight into additional technology needs and cultural barriers which are currently impeding the transition of the technology into operational environments. Proposed methods which addresses technology evolution and implementation are also discussed.
Directory of Open Access Journals (Sweden)
Sase Yuji
2011-09-01
Full Text Available Abstract Background Since the shift from a radiographic film-based system to that of a filmless system, the change in radiographic examination costs and costs structure have been undetermined. The activity-based costing (ABC method measures the cost and performance of activities, resources, and cost objects. The purpose of this study is to identify the cost structure of a radiographic examination comparing a filmless system to that of a film-based system using the ABC method. Methods We calculated the costs of radiographic examinations for both a filmless and a film-based system, and assessed the costs or cost components by simulating radiographic examinations in a health clinic. The cost objects of the radiographic examinations included lumbar (six views, knee (three views, wrist (two views, and other. Indirect costs were allocated to cost objects using the ABC method. Results The costs of a radiographic examination using a filmless system are as follows: lumbar 2,085 yen; knee 1,599 yen; wrist 1,165 yen; and other 1,641 yen. The costs for a film-based system are: lumbar 3,407 yen; knee 2,257 yen; wrist 1,602 yen; and other 2,521 yen. The primary activities were "calling patient," "explanation of scan," "take photographs," and "aftercare" for both filmless and film-based systems. The cost of these activities cost represented 36.0% of the total cost for a filmless system and 23.6% of a film-based system. Conclusions The costs of radiographic examinations using a filmless system and a film-based system were calculated using the ABC method. Our results provide clear evidence that the filmless system is more effective than the film-based system in providing greater value services directly to patients.
Muto, Hiroshi; Tani, Yuji; Suzuki, Shigemasa; Yokooka, Yuki; Abe, Tamotsu; Sase, Yuji; Terashita, Takayoshi; Ogasawara, Katsuhiko
2011-09-30
Since the shift from a radiographic film-based system to that of a filmless system, the change in radiographic examination costs and costs structure have been undetermined. The activity-based costing (ABC) method measures the cost and performance of activities, resources, and cost objects. The purpose of this study is to identify the cost structure of a radiographic examination comparing a filmless system to that of a film-based system using the ABC method. We calculated the costs of radiographic examinations for both a filmless and a film-based system, and assessed the costs or cost components by simulating radiographic examinations in a health clinic. The cost objects of the radiographic examinations included lumbar (six views), knee (three views), wrist (two views), and other. Indirect costs were allocated to cost objects using the ABC method. The costs of a radiographic examination using a filmless system are as follows: lumbar 2,085 yen; knee 1,599 yen; wrist 1,165 yen; and other 1,641 yen. The costs for a film-based system are: lumbar 3,407 yen; knee 2,257 yen; wrist 1,602 yen; and other 2,521 yen. The primary activities were "calling patient," "explanation of scan," "take photographs," and "aftercare" for both filmless and film-based systems. The cost of these activities cost represented 36.0% of the total cost for a filmless system and 23.6% of a film-based system. The costs of radiographic examinations using a filmless system and a film-based system were calculated using the ABC method. Our results provide clear evidence that the filmless system is more effective than the film-based system in providing greater value services directly to patients.
International Nuclear Information System (INIS)
Jones-Lee, M.; Aven, T.
2009-01-01
Social cost-benefit analysis is a well-established method for guiding decisions about safety investments, particularly in situations in which it is possible to make accurate predictions of future performance. However, its direct applicability to situations involving large degrees of uncertainty is less obvious and this raises the question of the extent to which social cost-benefit analysis can provide a useful input to the decision framework that has been explicitly developed to deal with safety decisions in which uncertainty is a major factor, namely risk analysis. This is the main focus of the arguments developed in this paper. In particular, we provide new insights by examining the fundamentals of both approaches and our principal conclusion is that social cost-benefit analysis and risk analysis represent complementary input bases to the decision-making process, and even in the case of large uncertainties social cost-benefit analysis may provide very useful decision support. What is required is the establishment of a proper contextual framework which structures and gives adequate weight to the uncertainties. An application to the possibility of a robbery at a cash depot is examined as a practical example.
AES, Automated Construction Cost Estimation System
International Nuclear Information System (INIS)
Holder, D.A.
1995-01-01
A - Description of program or function: AES (Automated Estimating System) enters and updates the detailed cost, schedule, contingency, and escalation information contained in a typical construction or other project cost estimates. It combines this information to calculate both un-escalated and escalated and cash flow values for the project. These costs can be reported at varying levels of detail. AES differs from previous versions in at least the following ways: The schedule is entered at the WBS-Participant, Activity level - multiple activities can be assigned to each WBS-Participant combination; the spending curve is defined at the schedule activity level and a weighing factor is defined which determines percentage of cost for the WBS-Participant applied to the schedule activity; Schedule by days instead of Fiscal Year/Quarter; Sales Tax is applied at the Line Item Level- a sales tax codes is selected to indicate Material, Large Single Item, or Professional Services; a 'data filter' has been added to allow user to define data the report is to be generated for. B - Method of solution: Average Escalation Rate: The average escalation for a Bill of is calculated in three steps. 1. A table of quarterly escalation factors is calculated based on the base fiscal year and quarter of the project entered in the estimate record and the annual escalation rates entered in the Standard Value File. 2. The percentage distribution of costs by quarter for the Bill of Material is calculated based on the schedule entered and the curve type. 3. The percent in each fiscal year and quarter in the distribution is multiplied by the escalation factor for the fiscal year and quarter. The sum of these results is the average escalation rate for that Bill of Material. Schedule by curve: The allocation of costs to specific time periods is dependent on three inputs, starting schedule date, ending schedule date, and the percentage of costs allocated to each quarter. Contingency Analysis: The
Wang, H.; Asefa, T.
2017-12-01
A real-time decision support tool (DST) for water supply system would consider system uncertainties, e.g., uncertain streamflow and demand, as well as operational constraints and infrastructure outage (e.g., pump station shutdown, an offline reservoir due to maintenance). Such DST is often used by water managers for resource allocation and delivery for customers. Although most seasonal DST used by water managers recognize those system uncertainties and operational constraints, most use only historical information or assume deterministic outlook of water supply systems. This study presents a seasonal DST that incorporates rainfall/streamflow uncertainties, seasonal demand outlook and system operational constraints. Large scale climate-information is captured through a rainfall simulator driven by a Bayesian non-homogeneous Markov Chain Monte Carlo model that allows non-stationary transition probabilities contingent on Nino 3.4 index. An ad-hoc seasonal demand forecasting model considers weather conditions explicitly and socio-economic factors implicitly. Latin Hypercube sampling is employed to effectively sample probability density functions of flow and demand. Seasonal system operation is modelled as a mixed-integer optimization problem that aims at minimizing operational costs. It embeds the flexibility of modifying operational rules at different components, e.g., surface water treatment plants, desalination facilities, and groundwater pumping stations. The proposed framework is illustrated at a wholesale water supplier in Southeastern United States, Tampa Bay Water. The use of the tool is demonstrated in proving operational guidance in a typical drawdown and refill cycle of a regional reservoir. The DST provided: 1) probabilistic outlook of reservoir storage and chance of a successful refill by the end of rainy season; 2) operational expectations for large infrastructures (e.g., high service pumps and booster stations) throughout the season. Other potential use
International Nuclear Information System (INIS)
Allison, C.M.; Hohorst, J.K.; Perez, M.; Reventos, F.
2010-01-01
The RELAP/SCDAPSIM/MOD4.0 code, designed to predict the behavior of reactor systems during normal and accident conditions, is being developed as part of the international SCDAP Development and Training Program (SDTP). RELAP/SCDAPSIM/MOD4.0, which is the first version of RELAP5 completely rewritten to FORTRAN 90/95/2000 standards, uses publicly available RELAP5 and SCDAP models in combination with advanced programming and numerical techniques and other SDTP-member modeling/user options. One such member developed option is an integrated uncertainty analysis package being developed jointly by the Technical University of Catalonia (UPC) and Innovative Systems Software (ISS). This paper briefly summarizes the features of RELAP/SCDAPSIM/MOD4.0 and the integrated uncertainty analysis package, and then presents an example of how the integrated uncertainty package can be setup and used for a simple pipe flow problem. (author)
International Nuclear Information System (INIS)
Xie, Y.L.; Li, Y.P.; Huang, G.H.; Li, Y.F.
2010-01-01
In this study, an interval fixed-mix stochastic programming (IFSP) model is developed for greenhouse gas (GHG) emissions reduction management under uncertainties. In the IFSP model, methods of interval-parameter programming (IPP) and fixed-mix stochastic programming (FSP) are introduced into an integer programming framework, such that the developed model can tackle uncertainties described in terms of interval values and probability distributions over a multi-stage context. Moreover, it can reflect dynamic decisions for facility-capacity expansion during the planning horizon. The developed model is applied to a case of planning GHG-emission mitigation, demonstrating that IFSP is applicable to reflecting complexities of multi-uncertainty, dynamic and interactive energy management systems, and capable of addressing the problem of GHG-emission reduction. A number of scenarios corresponding to different GHG-emission mitigation levels are examined; the results suggest that reasonable solutions have been generated. They can be used for generating plans for energy resource/electricity allocation and capacity expansion and help decision makers identify desired GHG mitigation policies under various economic costs and environmental requirements.
International Nuclear Information System (INIS)
Kim, Kihyung; Spakovsky, Michael R. von; Wang, M.; Nelson, Douglas J.
2011-01-01
During system development, large-scale, complex energy systems require multi-disciplinary efforts to achieve system quality, cost, and performance goals. As systems become larger and more complex, the number of possible system configurations and technologies, which meet the designer's objectives optimally, increases greatly. In addition, both transient and environmental effects may need to be taken into account. Thus, the difficulty of developing the system via the formulation of a single optimization problem in which the optimal synthesis/design and operation/control of the system are achieved simultaneously is great and rather problematic. This difficulty is further heightened with the introduction of uncertainty analysis, which transforms the problem from a purely deterministic one into a probabilistic one. Uncertainties, system complexity and nonlinearity, and large numbers of decision variables quickly render the single optimization problem unsolvable by conventional, single-level, optimization strategies. To address these difficulties, the strategy adopted here combines a dynamic physical decomposition technique for large-scale optimization with a response sensitivity analysis method for quantifying system response uncertainties to given uncertainty sources. The feasibility of such a hybrid approach is established by applying it to the synthesis/design and operation/control of a 5 kW proton exchange membrane (PEM) fuel cell system.
Historical Cost Growth of Completed Weapon System Programs
National Research Council Canada - National Science Library
Arena, Mark V; Leonard, Robert S; Murray, Sheila E; Younossi, Obaid
2006-01-01
...: Cost Risk Analysis for Air Force Systems," and includes a literature review of cost growth studies and a more extensive analysis of the historical cost growth in acquisition programs than appears...
ASSESSMENT OF UNCERTAINTY IN THE RADIATION DOSES FOR THE TECHA RIVER DOSIMETRY SYSTEM
Energy Technology Data Exchange (ETDEWEB)
Napier, Bruce A.; Degteva, M. O.; Anspaugh, L. R.; Shagina, N. B.
2009-10-23
In order to provide more accurate and precise estimates of individual dose (and thus more precise estimates of radiation risk) for the members of the ETRC, a new dosimetric calculation system, the Techa River Dosimetry System-2009 (TRDS-2009) has been prepared. The deterministic version of the improved dosimetry system TRDS-2009D was basically completed in April 2009. Recent developments in evaluation of dose-response models in light of uncertain dose have highlighted the importance of different types of uncertainties in the development of individual dose estimates. These include uncertain parameters that may be either shared or unshared within the dosimetric cohort, and also the nature of the type of uncertainty as aleatory or epistemic and either classical or Berkson. This report identifies the nature of the various input parameters and calculational methods incorporated in the Techa River Dosimetry System (based on the TRDS-2009D implementation), with the intention of preparing a stochastic version to estimate the uncertainties in the dose estimates. This report reviews the equations, databases, and input parameters, and then identifies the author’s interpretations of their general nature. It presents the approach selected so that the stochastic, Monte-Carlo, implementation of the dosimetry System - TRDS-2009MC - will provide useful information regarding the uncertainties of the doses.
Rhodes, C. R.; Sinha, P.; Amanda, N.
2013-12-01
In recent years the gap between what scientists know and what policymakers should appreciate in environmental decision making has received more attention, as the costs of the disconnect have become more apparent to both groups. Particularly for water-related policies, the EPA's Office of Water has struggled with benefit estimates held low by the inability to quantify ecological and economic effects that theory, modeling, and anecdotal or isolated case evidence suggest may prove to be larger. Better coordination with ecologists and hydrologists is being explored as a solution. The ecosystem services (ES) concept now nearly two decades old links ecosystem functions and processes to the human value system. But there remains no clear mapping of which ecosystem goods and services affect which individual or economic values. The National Ecosystem Services Classification System (NESCS, 'nexus') project brings together ecologists, hydrologists, and social scientists to do this mapping for aquatic and other ecosystem service-generating systems. The objective is to greatly reduce the uncertainty in water-related policy making by mapping and ultimately quantifying the various functions and products of aquatic systems, as well as how changes to aquatic systems impact the human economy and individual levels of non-monetary appreciation for those functions and products. Primary challenges to fostering interaction between scientists, social scientists, and policymakers are lack of a common vocabulary, and the need for a cohesive comprehensive framework that organizes concepts across disciplines and accommodates scientific data from a range of sources. NESCS builds the vocabulary and the framework so both may inform a scalable transdisciplinary policy-making application. This talk presents for discussion the process and progress in developing both this vocabulary and a classifying framework capable of bridging the gap between a newer but existing ecosystem services classification
Cost Optimal System Identification Experiment Design
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning
A structural system identification experiment design method is formulated in the light of decision theory, structural reliability theory and optimization theory. The experiment design is based on a preposterior analysis, well-known from the classical decision theory. I.e. the decisions concerning...... reflecting the cost of the experiment and the value of obtained additional information. An example concerning design of an experiment for parametric identification of a single degree of freedom structural system shows the applicability of the experiment design method....... the experiment design are not based on obtained experimental data. Instead the decisions are based on the expected experimental data assumed to be obtained from the measurements, estimated based on prior information and engineering judgement. The design method provides a system identification experiment design...
International Nuclear Information System (INIS)
Lujano-Rojas, Juan M.; Dufo-López, Rodolfo; Bernal-Agustín, José L.
2012-01-01
Highlights: ► We propose a mathematical model for optimal sizing of small wind energy systems. ► No other previous work has considered all the aspects included in this paper. ► The model considers several parameters about batteries. ► Wind speed variability is considered by means of ARMA model. ► The results show how to minimize the expected energy that is not supplied. - Abstract: In this paper, a mathematical model for stochastic simulation and optimization of small wind energy systems is presented. This model is able to consider the operation of the charge controller, the coulombic efficiency during charge and discharge processes, the influence of temperature on the battery bank capacity, the wind speed variability, and load uncertainty. The joint effect of charge controller operation, ambient temperature, and coulombic efficiency is analyzed in a system installed in Zaragoza (Spain), concluding that if the analysis without considering these factors is carried out, the reliability level of the physical system could be lower than expected, and an increment of 25% in the battery bank capacity would be required to reach a reliability level of 90% in the analyzed case. Also, the effect of the wind speed variability and load uncertainty in the system reliability is analyzed. Finally, the uncertainty in the battery bank lifetime and its effect on the net present cost are discussed. The results showed that, considering uncertainty of 17.5% in the battery bank lifetime calculated using the Ah throughput model, about 12% of uncertainty in the net present cost is expected. The model presented in this research could be a useful stochastic simulation and optimization tool that allows the consideration of important uncertainty factors in techno-economic analysis.
Avoided operating costs in thermal generating systems
International Nuclear Information System (INIS)
Chowdhury, N.; Billinton, R.; Gupta, R.
1995-01-01
A simple and straightforward technique was developed to assess avoided system operating costs associated with non-utility generation (NUG). The technique was based on optimum loading configurations of the committed units both before and after the inclusion of NUG energy. The salient features of the technique were presented in this paper. Assessment of avoided operating cost with deterministic and probabilistic criteria were explained. A time differentiated price system was adopted in the algorithms to reflect the different value placed on purchased price by a utility at different times of the day. The algorithms show the utility effects of dispatchable and non-dispatchable NUG energies. The IEEE Reliability Test System (RTS) was utilized for numerical analysis. Results were illustrated. It was found that sensitivity studies similar to those performed on the IEEE-RTS could be utilized to determine the amount of energy and the time period during which utilities and NUGs can maximize their economic benefits. 7 refs., 5 figs., 1 tab
On Inventory Control For Perishable Inventory Systems Subject To Uncertainties On Customer Demands
Abbou , Rosa; Loiseau , Jean-Jacques; Khaldi , Hajer; Farraa , Berna ,
2017-01-01
International audience; This paper deals with the inventory controller design for constrained production systems subject to uncertainties on the customer demands. The case study focuses on the inventory regulation problem in production systems where contain perishable finite products. Such systems are characterized by the presence of delays due to production processes, and constraints from the instantaneous inventory level, production level and the finite capacities of stocks. To do that, we ...
Modelling sensitivity and uncertainty in a LCA model for waste management systems - EASETECH
DEFF Research Database (Denmark)
Damgaard, Anders; Clavreul, Julie; Baumeister, Hubert
2013-01-01
In the new model, EASETECH, developed for LCA modelling of waste management systems, a general approach for sensitivity and uncertainty assessment for waste management studies has been implemented. First general contribution analysis is done through a regular interpretation of inventory and impact...
Best Response Bayesian Reinforcement Learning for Multiagent Systems with State Uncertainty
Oliehoek, F.A.; Amato, C.
2014-01-01
It is often assumed that agents in multiagent systems with state uncertainty have full knowledge of the model of dy- namics and sensors, but in many cases this is not feasible. A more realistic assumption is that agents must learn about the environment and other agents while acting. Bayesian methods
Synchronization of chaotic systems with parameter uncertainties via variable structure control
International Nuclear Information System (INIS)
Etemadi, Shahram; Alasty, Aria; Salarieh, Hassan
2006-01-01
The Letter introduces a robust control design method to synchronize a pair of different uncertain chaotic systems. The technique is based on sliding-mode and variable structure control theories. Comparison of proposed method with previous works is performed during simulations. It is shown that the proposed controller while appearing in a faster response, is able to overcome random uncertainties of all model parameters
Yang, Z.; Cauberg, J.J.M.; Tenpierik, M.J.
2012-01-01
Both critical and optimistic claims have been made regarding the performance of heat recovery ventilation systems (HRVS) in dwellings. Such arguments are raised partly because two key aspects are not fully clarified, i.e. the performance criteria and the influence of uncertainties. In the current
Marie, I. A.; Sugiarto, D.; Surjasa, D.; Witonohadi, A.
2018-01-01
Automotive battery supply chain include battery manufacturer, sulphuric acid suppliers, polypropylene suppliers, lead suppliers, transportation service providers, warehouses, retailers and even customers. Due to the increasingly dynamic condition of the environment, supply chain actors were required to improve their ability to overcome various uncertainty issues in the environment. This paper aims to describe the process of designing a knowledge management system for risk mitigation in supply chain uncertainty. The design methodology began with the identification of the knowledge needed to solve the problems associated with uncertainty and analysis of system requirements. The design of the knowledge management system was described in the form of a data flow diagram. The results of the study indicated that key knowledge area that needs to be managed were the knowledge to maintain the stability of process in sulphuric acid process and knowledge to overcome the wastes in battery manufacturing process. The system was expected to be a media acquisition, dissemination and storage of knowledge associated with the uncertainty in the battery supply chain and increase the supply chain performance.
Steinbuch, M.; Terlouw, J.C.; Bosgra, O.H.; Smit, S.G.
1992-01-01
The investigation of closed-loop systems subject to model perturbations is an important issue to assure stability robustness of a control design. A large variety of model perturbations can be described by norm-bounded uncertainty models. A general approach for modelling structured complex and
Synchronization of chaotic systems with parameter uncertainties via variable structure control
Energy Technology Data Exchange (ETDEWEB)
Etemadi, Shahram [Centre of Excellence in Design, Robotics and Automation (CEDRA), School of Mechanical Engineering, Sharif University of Technology, Tehran (Iran, Islamic Republic of); Alasty, Aria [Centre of Excellence in Design, Robotics and Automation (CEDRA), School of Mechanical Engineering, Sharif University of Technology, Tehran (Iran, Islamic Republic of)]. E-mail: aalasti@sharif.edu; Salarieh, Hassan [Centre of Excellence in Design, Robotics and Automation (CEDRA), School of Mechanical Engineering, Sharif University of Technology, Tehran (Iran, Islamic Republic of)
2006-08-28
The Letter introduces a robust control design method to synchronize a pair of different uncertain chaotic systems. The technique is based on sliding-mode and variable structure control theories. Comparison of proposed method with previous works is performed during simulations. It is shown that the proposed controller while appearing in a faster response, is able to overcome random uncertainties of all model parameters.
H∞ Loop Shaping Control of Input Saturated Systems with Norm-Bounded Parametric Uncertainty
Directory of Open Access Journals (Sweden)
Renan Lima Pereira
2015-01-01
Full Text Available This paper proposes a gain-scheduling control design strategy for a class of linear systems with the presence of both input saturation constraints and norm-bounded parametric uncertainty. LMI conditions are derived in order to obtain a gain-scheduled controller that ensures the robust stability and performance of the closed loop system. The main steps to obtain such a controller are given. Differently from other gain-scheduled approaches in the literature, this one focuses on the problem of H∞ loop shaping control design with input saturation nonlinearity and norm-bounded uncertainty to reduce the effect of the disturbance input on the controlled outputs. Here, the design problem has been formulated in the four-block H∞ synthesis framework, in which it is possible to describe the parametric uncertainty and the input saturation nonlinearity as perturbations to normalized coprime factors of the shaped plant. As a result, the shaped plant is represented as a linear parameter-varying (LPV system while the norm-bounded uncertainty and input saturation are incorporated. This procedure yields a linear parameter-varying structure for the controller that ensures the stability of the polytopic LPV shaped plant from the vertex property. Finally, the effectiveness of the method is illustrated through application to a physical system: a VTOL “vertical taking-off landing” helicopter.
Stochastic long term modelling of a drainage system with estimation of return period uncertainty
DEFF Research Database (Denmark)
Thorndahl, Søren
2009-01-01
Long term prediction of maximum water levels and combined sewer overflow (CSO) in drainage systems are associated with large uncertainties. Especially on rainfall inputs, parameters, and assessment of return periods. This paper proposes a Monte Carlo based methodology for stochastic prediction of...
Uncertainty evaluation of reliability of shutdown system of a medium size fast breeder reactor
Energy Technology Data Exchange (ETDEWEB)
Zeliang, Chireuding; Singh, Om Pal, E-mail: singhop@iitk.ac.in; Munshi, Prabhat
2016-11-15
Highlights: • Uncertainty analysis of reliability of Shutdown System is carried out. • Monte Carlo method of sampling is used. • The effect of various reliability improvement measures of SDS are accounted. - Abstract: In this paper, results are presented on the uncertainty evaluation of the reliability of Shutdown System (SDS) of a Medium Size Fast Breeder Reactor (MSFBR). The reliability analysis results are of Kumar et al. (2005). The failure rate of the components of SDS are taken from International literature and it is assumed that these follow log-normal distribution. Fault tree method is employed to propagate the uncertainty in failure rate from components level to shutdown system level. The beta factor model is used to account different extent of diversity. The Monte Carlo sampling technique is used for the analysis. The results of uncertainty analysis are presented in terms of the probability density function, cumulative distribution function, mean, variance, percentile values, confidence intervals, etc. It is observed that the spread in the probability distribution of SDS failure rate is less than SDS components failure rate and ninety percent values of the failure rate of SDS falls below the target value. As generic values of failure rates are used, sensitivity analysis is performed with respect to failure rate of control and safety rods and beta factor. It is discovered that a large increase in failure rate of SDS rods is not carried to SDS system failure proportionately. The failure rate of SDS is very sensitive to the beta factor of common cause failure between the two systems of SDS. The results of the study provide insight in the propagation of uncertainty in the failure rate of SDS components to failure rate of shutdown system.
Scenario-based fitted Q-iteration for adaptive control of water reservoir systems under uncertainty
Bertoni, Federica; Giuliani, Matteo; Castelletti, Andrea
2017-04-01
Over recent years, mathematical models have largely been used to support planning and management of water resources systems. Yet, the increasing uncertainties in their inputs - due to increased variability in the hydrological regimes - are a major challenge to the optimal operations of these systems. Such uncertainty, boosted by projected changing climate, violates the stationarity principle generally used for describing hydro-meteorological processes, which assumes time persisting statistical characteristics of a given variable as inferred by historical data. As this principle is unlikely to be valid in the future, the probability density function used for modeling stochastic disturbances (e.g., inflows) becomes an additional uncertain parameter of the problem, which can be described in a deterministic and set-membership based fashion. This study contributes a novel method for designing optimal, adaptive policies for controlling water reservoir systems under climate-related uncertainty. The proposed method, called scenario-based Fitted Q-Iteration (sFQI), extends the original Fitted Q-Iteration algorithm by enlarging the state space to include the space of the uncertain system's parameters (i.e., the uncertain climate scenarios). As a result, sFQI embeds the set-membership uncertainty of the future inflow scenarios in the action-value function and is able to approximate, with a single learning process, the optimal control policy associated to any scenario included in the uncertainty set. The method is demonstrated on a synthetic water system, consisting of a regulated lake operated for ensuring reliable water supply to downstream users. Numerical results show that the sFQI algorithm successfully identifies adaptive solutions to operate the system under different inflow scenarios, which outperform the control policy designed under historical conditions. Moreover, the sFQI policy generalizes over inflow scenarios not directly experienced during the policy design
Latency and Criticality of Uncertainties in the Development of Product-Service Systems
DEFF Research Database (Denmark)
Ramirez Hernandez, Tabea; Kreye, Melanie; Pigosso, Daniela Cristina Antelmi
2018-01-01
Servitization requires manufacturers to develop new business models - compound offerings between products and services often referred to as Product-Service Systems (PSS). The development of PSS goes beyond the traditional product-development practices, requiring new processes and capabilities due...... to the high levels of uncertainty caused by the novelty and complexity of developing the product and the service in parallel. Uncertainty is further increased through mostly long life cycles of PSS and organisational complexity caused by a high degree of stakeholder involvement (Wolfenstetter et al., 2015...
A Belief Rule Based Expert System to Assess Mental Disorder under Uncertainty
DEFF Research Database (Denmark)
Hossain, Mohammad Shahadat; Afif Monrat, Ahmed; Hasan, Mamun
2016-01-01
to ignorance, incompleteness, and randomness. So, a belief rule-based expert system (BRBES) has been designed and developed with the capability of handling the uncertainties mentioned. Evidential reasoning works as the inference engine and the belief rule base as the knowledge representation schema......Mental disorder is a change of mental or behavioral pattern that causes sufferings and impairs the ability to function in ordinary life. In psychopathology, the assessment methods of mental disorder contain various types of uncertainties associated with signs and symptoms. This study identifies...
Bertrand-Krajewski, J L; Bardin, J P; Mourad, M; Béranger, Y
2003-01-01
Assessing the functioning and the performance of urban drainage systems on both rainfall event and yearly time scales is usually based on online measurements of flow rates and on samples of influent effluent for some rainfall events per year. In order to draw pertinent scientific and operational conclusions from the measurement results, it is absolutely necessary to use appropriate methods and techniques in order to i) calibrate sensors and analytical methods, ii) validate raw data, iii) evaluate measurement uncertainties, iv) evaluate the number of rainfall events to sample per year in order to determine performance indicator with a given uncertainty. Based an previous work, the paper gives a synthetic review of required and techniques, and illustrates their application to storage and settling tanks. Experiments show that, controlled and careful experimental conditions, relative uncertainties are about 20% for flow rates in sewer pipes, 6-10% for volumes, 25-35% for TSS concentrations and loads, and 18-276% for TSS removal rates. In order to evaluate the annual pollutant interception efficiency of storage and settling tanks with a given uncertainty, efforts should first be devoted to decrease the sampling uncertainty by increasing the number of sampled events.
An Overview of Physical Layer Security in Wireless Communication Systems With CSIT Uncertainty
Hyadi, Amal; Rezki, Zouheir; Alouini, Mohamed-Slim
2016-01-01
The concept of physical layer security builds on the pivotal idea of turning the channel's imperfections, such as noise and fading, into a source of security. This is established through appropriately designed coding techniques and signal processing strategies. In this vein, it has been shown that fading channels can enhance the transmission of confidential information and that a secure communication can be achieved even when the channel to the eavesdropper is better than the main channel. However, to fully benefit from what fading has to offer, the knowledge of the channel state information at the transmitter (CSIT) is of primordial importance. In practical wireless communication systems, CSIT is usually obtained, prior to data transmission, through CSI feedback sent by the receivers. The channel links over which this feedback information is sent can be either noisy, rate-limited, or delayed, leading to CSIT uncertainty. In this paper, we present a comprehensive review of recent and ongoing research works on physical layer security with CSIT uncertainty. We focus on both information theoretic and signal processing approaches to the topic when the uncertainty concerns the channel to the wiretapper or the channel to the legitimate receiver. Moreover, we present a classification of the research works based on the considered channel uncertainty. Mainly, we distinguish between the cases when the uncertainty comes from an estimation error of the CSIT, from a CSI feedback link with limited capacity, or from an outdated CSI.
An Overview of Physical Layer Security in Wireless Communication Systems With CSIT Uncertainty
Hyadi, Amal
2016-09-21
The concept of physical layer security builds on the pivotal idea of turning the channel\\'s imperfections, such as noise and fading, into a source of security. This is established through appropriately designed coding techniques and signal processing strategies. In this vein, it has been shown that fading channels can enhance the transmission of confidential information and that a secure communication can be achieved even when the channel to the eavesdropper is better than the main channel. However, to fully benefit from what fading has to offer, the knowledge of the channel state information at the transmitter (CSIT) is of primordial importance. In practical wireless communication systems, CSIT is usually obtained, prior to data transmission, through CSI feedback sent by the receivers. The channel links over which this feedback information is sent can be either noisy, rate-limited, or delayed, leading to CSIT uncertainty. In this paper, we present a comprehensive review of recent and ongoing research works on physical layer security with CSIT uncertainty. We focus on both information theoretic and signal processing approaches to the topic when the uncertainty concerns the channel to the wiretapper or the channel to the legitimate receiver. Moreover, we present a classification of the research works based on the considered channel uncertainty. Mainly, we distinguish between the cases when the uncertainty comes from an estimation error of the CSIT, from a CSI feedback link with limited capacity, or from an outdated CSI.
A phantom-based study for assessing the error and uncertainty of a neuronavigation system
Directory of Open Access Journals (Sweden)
Natalia Izquierdo-Cifuentes
2017-01-01
Full Text Available This document describes a calibration protocol with the intention to introduce a guide to standardize the metrological vocabulary among manufacturers of image-guided surgery systems. Two stages were developed to measure the errors and estimate the uncertainty of a neuronavigator in different situations, on the first one it was determined a mechanical error on a virtual model of an acrylic phantom, on the second it was determined a coordinate error on the computerized axial tomography scan of the same phantom. Ten standard coordinates of the phantom were compared with the coordinates generated by the NeuroCPS. After measurement model was established, there were identified the sources of uncertainty and the data was processed according the guide to the expression of uncertainty in measurement.
Wood, Alexander
2004-01-01
deterministic methods for Hg TMDL decision support, one that is fully compatible with an adaptive management approach. This alternative approach uses empirical data and informed judgment to provide a scientific and technical basis for helping National Pollutant Discharge Elimination System (NPDES) permit holders make management decisions. An Hg-offset system would be an option if a wastewater-treatment plant could not achieve NPDES permit requirements for HgT reduction. We develop a probabilistic decision-analytical model consisting of three submodels for HgT loading, MeHg, and cost mitigation within a Bayesian network that integrates information of varying rigor and detail into a simple model of a complex system. Hg processes are identified and quantified by using a combination of historical data, statistical models, and expert judgment. Such an integrated approach to uncertainty analysis allows easy updating of prediction and inference when observations of model variables are made. We demonstrate our approach with data from the Cache Creek watershed (a subbasin of the Sacramento River watershed). The empirical models used to generate the needed probability distributions are based on the same empirical models currently being used by the Central Valley Regional Water Quality Control Cache Creek Hg TMDL working group. The significant difference is that input uncertainty and error are explicitly included in the model and propagated throughout its algorithms. This work demonstrates how to integrate uncertainty into the complex and highly uncertain Hg TMDL decisionmaking process. The various sources of uncertainty are propagated as decision risk that allows decisionmakers to simultaneously consider uncertainties in remediation/implementation costs while attempting to meet environmental/ecologic targets. We must note that this research is on going. As more data are collected, the HgT and cost-mitigation submodels are updated and the uncer
Cost benefit risk - a concept for management of integrated urban wastewater systems?
DEFF Research Database (Denmark)
Hauger, Mikkel B.; Rauch, W.; Linde, Jens Jørgen
2002-01-01
Urban wastewater systems should be evaluated and analysed from an integrated point of view, taking all parts of the system, that is sewer system, wastewater treatment plant and receiving waters into consideration. Risk and parameter uncertainties are aspects that hardly ever have been addressed...... in the evaluation and design of urban wastewater systems. In this paper we present and discuss a probabilistic approach for evaluation of the performance of urban wastewater systems. Risk analysis together with the traditional cost-benefit analysis is a special variant of multi-criteria analysis that seeks to find...... the most feasible improvement alternative for an urban wastewater system. The most feasible alternative in this context is the alternative that has the best performance, meaning that the alternative has the lowest sum of costs, benefits and risks. The sum is expressed as the Net Present Cost (NPC). To use...
Principles and methods of managerial cost-accounting systems.
Suver, J D; Cooper, J C
1988-01-01
An introduction to cost-accounting systems for pharmacy managers is provided; terms are defined and examples of specific applications are given. Cost-accounting systems determine, record, and report the resources consumed in providing services. An effective cost-accounting system must provide the information needed for both internal and external reports. In accounting terms, cost is the value given up to secure an asset. In determining how volumes of activity affect costs, fixed costs and variable costs are calculated; applications include pricing strategies, cost determinations, and break-even analysis. Also discussed are the concepts of direct and indirect costs, opportunity costs, and incremental and sunk costs. For most pharmacy department services, process costing, an accounting of intermediate outputs and homogeneous units, is used; in determining the full cost of providing a product or service (e.g., patient stay), job-order costing is used. Development of work-performance standards is necessary for monitoring productivity and determining product costs. In allocating pharmacy department costs, a ratio of costs to charges can be used; this method is convenient, but microcosting (specific identification of the costs of products) is more accurate. Pharmacy managers can use cost-accounting systems to evaluate the pharmacy's strategies, policies, and services and to improve budgets and reports.
Operational cost minimization in cooling water systems
Directory of Open Access Journals (Sweden)
Castro M.M.
2000-01-01
Full Text Available In this work, an optimization model that considers thermal and hydraulic interactions is developed for a cooling water system. It is a closed loop consisting of a cooling tower unit, circulation pump, blower and heat exchanger-pipe network. Aside from process disturbances, climatic fluctuations are considered. Model constraints include relations concerning tower performance, air flowrate requirement, make-up flowrate, circulating pump performance, heat load in each cooler, pressure drop constraints and climatic conditions. The objective function is operating cost minimization. Optimization variables are air flowrate, forced water withdrawal upstream the tower, and valve adjustment in each branch. It is found that the most significant operating cost is related to electricity. However, for cooled water temperatures lower than a specific target, there must be a forced withdrawal of circulating water and further makeup to enhance the cooling tower capacity. Additionally, the system is optimized along the months. The results corroborate the fact that the most important variable on cooling tower performance is not the air temperature itself, but its humidity.
International Nuclear Information System (INIS)
Blackwood, L.G.; Harker, Y.D.; Meachum, T.R.
1997-12-01
The Idaho National Engineering and Environmental Laboratory is being used as a temporary storage facility for transuranic waste generated by the US Nuclear Weapons program at the Rocky Flats Plant (RFP) in Golden, Colorado. Currently, there is a large effort in progress to prepare to ship this waste to the Waste Isolation Pilot Plant (WIPP) in Carlsbad, New Mexico. In order to meet the TRU Waste Characterization Quality Assurance Program Plan nondestructive assay compliance requirements and quality assurance objectives, it is necessary to determine the total uncertainty of the radioassay results produced by the Stored Waste Examination Pilot Plant (SWEPP) Passive Active Neutron (PAN) radioassay system. This paper is one of a series of reports quantifying the results of the uncertainty analysis of the PAN system measurements for specific waste types and measurement modes. In particular this report covers active mode measurements of weapons grade plutonium-contaminated aqueous sludge waste contained in 208 liter drums (item description codes 1, 2, 7, 800, 803, and 807). Results of the uncertainty analysis for PAN active mode measurements of aqueous sludge indicate that a bias correction multiplier of 1.55 should be applied to the PAN aqueous sludge measurements. With the bias correction, the uncertainty bounds on the expected bias are 0 ± 27%. These bounds meet the Quality Assurance Program Plan requirements for radioassay systems
International Nuclear Information System (INIS)
Rocco Sanseverino, Claudio M.; Ramirez-Marquez, José Emmanuel
2014-01-01
The reliability of a system, notwithstanding it intended function, can be significantly affected by the uncertainty in the reliability estimate of the components that define the system. This paper implements the Unscented Transformation to quantify the effects of the uncertainty of component reliability through two approaches. The first approach is based on the concept of uncertainty propagation, which is the assessment of the effect that the variability of the component reliabilities produces on the variance of the system reliability. This assessment based on UT has been previously considered in the literature but only for system represented through series/parallel configuration. In this paper the assessment is extended to systems whose reliability cannot be represented through analytical expressions and require, for example, Monte Carlo Simulation. The second approach consists on the evaluation of the importance of components, i.e., the evaluation of the components that most contribute to the variance of the system reliability. An extension of the UT is proposed to evaluate the so called “main effects” of each component, as well to assess high order component interaction. Several examples with excellent results illustrate the proposed approach. - Highlights: • Simulation based approach for computing reliability estimates. • Computation of reliability variance via 2n+1 points. • Immediate computation of component importance. • Application to network systems
Uncertainties Related to Extreme Event Statistics of Sewer System Surcharge and Overflow
DEFF Research Database (Denmark)
Schaarup-Jensen, Kjeld; Johansen, C.; Thorndahl, Søren Liedtke
2005-01-01
Today it is common practice - in the major part of Europe - to base design of sewer systems in urban areas on recommended minimum values of flooding frequencies related to either pipe top level, basement level in buildings or level of road surfaces. Thus storm water runoff in sewer systems is only...... proceeding in an acceptable manner, if flooding of these levels is having an average return period bigger than a predefined value. This practice is also often used in functional analysis of existing sewer systems. If a sewer system can fulfil recommended flooding frequencies or not, can only be verified...... by performing long term simulations - using a sewer flow simulation model - and draw up extreme event statistics from the model simulations. In this context it is important to realize that uncertainties related to the input parameters of rainfall runoff models will give rise to uncertainties related...
Robust stabilisation of time-varying delay systems with probabilistic uncertainties
Jiang, Ning; Xiong, Junlin; Lam, James
2016-09-01
For robust stabilisation of time-varying delay systems, only sufficient conditions are available to date. A natural question is as follows: if the existing sufficient conditions are not satisfied, and hence no controllers can be found, what can one do to improve the stability performance of time-varying delay systems? This question is addressed in this paper when there is a probabilistic structure on the parameter uncertainty set. A randomised algorithm is proposed to design a state-feedback controller, which stabilises the system over the uncertainty domain in a probabilistic sense. The capability of the designed controller is quantified by the probability of stability of the resulting closed-loop system. The accuracy of the solution obtained from the randomised algorithm is also analysed. Finally, numerical examples are used to illustrate the effectiveness and advantages of the developed controller design approach.
Optimized production planning model for a multi-plant cultivation system under uncertainty
Ke, Shunkui; Guo, Doudou; Niu, Qingliang; Huang, Danfeng
2015-02-01
An inexact multi-constraint programming model under uncertainty was developed by incorporating a production plan algorithm into the crop production optimization framework under the multi-plant collaborative cultivation system. In the production plan, orders from the customers are assigned to a suitable plant under the constraints of plant capabilities and uncertainty parameters to maximize profit and achieve customer satisfaction. The developed model and solution method were applied to a case study of a multi-plant collaborative cultivation system to verify its applicability. As determined in the case analysis involving different orders from customers, the period of plant production planning and the interval between orders can significantly affect system benefits. Through the analysis of uncertain parameters, reliable and practical decisions can be generated using the suggested model of a multi-plant collaborative cultivation system.
SURE: a system of computer codes for performing sensitivity/uncertainty analyses with the RELAP code
International Nuclear Information System (INIS)
Bjerke, M.A.
1983-02-01
A package of computer codes has been developed to perform a nonlinear uncertainty analysis on transient thermal-hydraulic systems which are modeled with the RELAP computer code. Using an uncertainty around the analyses of experiments in the PWR-BDHT Separate Effects Program at Oak Ridge National Laboratory. The use of FORTRAN programs running interactively on the PDP-10 computer has made the system very easy to use and provided great flexibility in the choice of processing paths. Several experiments simulating a loss-of-coolant accident in a nuclear reactor have been successfully analyzed. It has been shown that the system can be automated easily to further simplify its use and that the conversion of the entire system to a base code other than RELAP is possible
Increased accuracy of cost-estimation using product configuration systems
DEFF Research Database (Denmark)
Rasmussen, Jeppe Bredahl; Hvam, Lars; Mortensen, Niels Henrik
This article describes an approach for utilizing Product Configuration Systems (PCS) for quantifying project costs in project-based companies. It presents a case study demonstrating a method of quantifying costs in a way that makes it possible to configure cost- and time estimates. Piecework costs......, material costs and sub-supplier costs are used as principle cost elements and linked to structural and process elements to facilitate configuration. The cost data are used by the PCS to generate fast and accurate cost-estimates, quotations, time estimates and cost summaries. The described cost...... quantification principles have been used in a Scandinavian SME (Small and Medium-sized Enterprise) since the 90’s, but have since 2011 been adopted to be used in a configuration system. A longitudinal case study was conducted to compare cost and time-estimation accuracy before and after implementation. We...
Directory of Open Access Journals (Sweden)
Mohammadtaghi Hamidi Beheshti
2010-01-01
Full Text Available We propose a fractional-order controller to stabilize unstable fractional-order open-loop systems with interval uncertainty whereas one does not need to change the poles of the closed-loop system in the proposed method. For this, we will use the robust stability theory of Fractional-Order Linear Time Invariant (FO-LTI systems. To determine the control parameters, one needs only a little knowledge about the plant and therefore, the proposed controller is a suitable choice in the control of interval nonlinear systems and especially in fractional-order chaotic systems. Finally numerical simulations are presented to show the effectiveness of the proposed controller.
Exploring the implication of climate process uncertainties within the Earth System Framework
Booth, B.; Lambert, F. H.; McNeal, D.; Harris, G.; Sexton, D.; Boulton, C.; Murphy, J.
2011-12-01
Uncertainties in the magnitude of future climate change have been a focus of a great deal of research. Much of the work with General Circulation Models has focused on the atmospheric response to changes in atmospheric composition, while other processes remain outside these frameworks. Here we introduce an ensemble of new simulations, based on an Earth System configuration of HadCM3C, designed to explored uncertainties in both physical (atmospheric, oceanic and aerosol physics) and carbon cycle processes, using perturbed parameter approaches previously used to explore atmospheric uncertainty. Framed in the context of the climate response to future changes in emissions, the resultant future projections represent significantly broader uncertainty than existing concentration driven GCM assessments. The systematic nature of the ensemble design enables interactions between components to be explored. For example, we show how metrics of physical processes (such as climate sensitivity) are also influenced carbon cycle parameters. The suggestion from this work is that carbon cycle processes represent a comparable contribution to uncertainty in future climate projections as contributions from atmospheric feedbacks more conventionally explored. The broad range of climate responses explored within these ensembles, rather than representing a reason for inaction, provide information on lower likelihood but high impact changes. For example while the majority of these simulations suggest that future Amazon forest extent is resilient to the projected climate changes, a small number simulate dramatic forest dieback. This ensemble represents a framework to examine these risks, breaking them down into physical processes (such as ocean temperature drivers of rainfall change) and vegetation processes (where uncertainties point towards requirements for new observational constraints).
Institute of Scientific and Technical Information of China (English)
XIA Yuanqing; HAN Jingqing
2005-01-01
This paper concerns robust Kalman filtering for systems under norm bounded uncertainties in all the system matrices and error covariance constraints. Sufficient conditions are given for the existence of such filters in terms of Riccati equations. The solutions to the conditions can be used to design the filters. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed design procedure.
Cost optimization for buildings with hybrid ventilation systems
Ji, Kun; Lu, Yan
2018-02-13
A method including: computing a total cost for a first zone in a building, wherein the total cost is equal to an actual energy cost of the first zone plus a thermal discomfort cost of the first zone; and heuristically optimizing the total cost to identify temperature setpoints for a mechanical heating/cooling system and a start time and an end time of the mechanical heating/cooling system, based on external weather data and occupancy data of the first zone.
Directory of Open Access Journals (Sweden)
Ying-Yi Hong
2015-03-01
Full Text Available This paper explores real power generation planning, considering distributed generation resources and energy storage in a small standalone power system. On account of the Kyoto Protocol and Copenhagen Accord, wind and photovoltaic (PV powers are considered as clean and renewable energies. In this study, a genetic algorithm (GA was used to determine the optimal capacities of wind-turbine-generators, PV, diesel generators and energy storage in a small standalone power system. The investment costs (installation, unit and maintenance costs of the distributed generation resources and energy storage and the cost of fuel for the diesel generators were minimized while the reliability requirement and CO2 emission limit were fulfilled. The renewable sources and loads were modeled by random variables because of their uncertainties. The equality and inequality constraints in the genetic algorithms were treated by cumulant effects and cumulative probability of random variables, respectively. The IEEE reliability data for an 8760 h load profile with a 150 kW peak load were used to demonstrate the applicability of the proposed method.
Robust framework for PET image reconstruction incorporating system and measurement uncertainties.
Directory of Open Access Journals (Sweden)
Huafeng Liu
Full Text Available In Positron Emission Tomography (PET, an optimal estimate of the radioactivity concentration is obtained from the measured emission data under certain criteria. So far, all the well-known statistical reconstruction algorithms require exactly known system probability matrix a priori, and the quality of such system model largely determines the quality of the reconstructed images. In this paper, we propose an algorithm for PET image reconstruction for the real world case where the PET system model is subject to uncertainties. The method counts PET reconstruction as a regularization problem and the image estimation is achieved by means of an uncertainty weighted least squares framework. The performance of our work is evaluated with the Shepp-Logan simulated and real phantom data, which demonstrates significant improvements in image quality over the least squares reconstruction efforts.
Zhang, Langwen; Xie, Wei; Wang, Jingcheng
2017-11-01
In this work, synthesis of robust distributed model predictive control (MPC) is presented for a class of linear systems subject to structured time-varying uncertainties. By decomposing a global system into smaller dimensional subsystems, a set of distributed MPC controllers, instead of a centralised controller, are designed. To ensure the robust stability of the closed-loop system with respect to model uncertainties, distributed state feedback laws are obtained by solving a min-max optimisation problem. The design of robust distributed MPC is then transformed into solving a minimisation optimisation problem with linear matrix inequality constraints. An iterative online algorithm with adjustable maximum iteration is proposed to coordinate the distributed controllers to achieve a global performance. The simulation results show the effectiveness of the proposed robust distributed MPC algorithm.
Energy Technology Data Exchange (ETDEWEB)
Tsao, Jeffrey Y. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Trucano, Timothy G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kleban, Stephen D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Naugle, Asmeret Bier [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Verzi, Stephen Joseph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Swiler, Laura Painton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Johnson, Curtis M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Smith, Mark A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Flanagan, Tatiana Paz [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vugrin, Eric D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gabert, Kasimir Georg [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lave, Matthew Samuel [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Chen, Wei [Northwestern Univ., Evanston, IL (United States); DeLaurentis, Daniel [Purdue Univ., West Lafayette, IN (United States); Hubler, Alfred [Univ. of Illinois, Urbana, IL (United States); Oberkampf, Bill [WLO Consulting, Austin, TX (United States)
2016-08-01
This report contains the written footprint of a Sandia-hosted workshop held in Albuquerque, New Mexico, June 22-23, 2016 on “Complex Systems Models and Their Applications: Towards a New Science of Verification, Validation and Uncertainty Quantification,” as well as of pre-work that fed into the workshop. The workshop’s intent was to explore and begin articulating research opportunities at the intersection between two important Sandia communities: the complex systems (CS) modeling community, and the verification, validation and uncertainty quantification (VVUQ) community The overarching research opportunity (and challenge) that we ultimately hope to address is: how can we quantify the credibility of knowledge gained from complex systems models, knowledge that is often incomplete and interim, but will nonetheless be used, sometimes in real-time, by decision makers?
Cost system design and cost management in the Spanish public sector
Boned, Josep Lluís; Bagur, Llorenç; Tayles, Mike
2006-01-01
Cost systems have been shown to have developed considerably in recent years and activity-based costing (ABC) has been shown to be a contribution to cost management, particularly in service businesses. The public sector is composed to a very great extent of service functions, yet considerably less has been reported of the use of ABC to support cost management in this sector. In Spain, cost systems are essential for city councils as they are obliged to calculate the cost of the services subject...
Incorporating Forecast Uncertainty in Utility Control Center
Energy Technology Data Exchange (ETDEWEB)
Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian
2014-07-09
Uncertainties in forecasting the output of intermittent resources such as wind and solar generation, as well as system loads are not adequately reflected in existing industry-grade tools used for transmission system management, generation commitment, dispatch and market operation. There are other sources of uncertainty such as uninstructed deviations of conventional generators from their dispatch set points, generator forced outages and failures to start up, load drops, losses of major transmission facilities and frequency variation. These uncertainties can cause deviations from the system balance, which sometimes require inefficient and costly last minute solutions in the near real-time timeframe. This Chapter considers sources of uncertainty and variability, overall system uncertainty model, a possible plan for transition from deterministic to probabilistic methods in planning and operations, and two examples of uncertainty-based fools for grid operations.This chapter is based on work conducted at the Pacific Northwest National Laboratory (PNNL)
Incremental cost analysis of advanced concept CAES systems
Energy Technology Data Exchange (ETDEWEB)
Knutsen, C.A.
1979-09-01
The costs of compressed air energy storage (CAES) systems using thermal energy storage (TES) are compared to the costs of CAES systems without TES and simple cycle gas turbine systems. Comparisons are made in terms of the system energy costs levelized over the operating life of the systems. These are in 1985 price levels which is the assumed first year of operation for the systems.
International Nuclear Information System (INIS)
Petruzzi, A.; D'Auria, F.; Cacuci, D.G.
2009-01-01
Nuclear Power Plant (NPP) technology has been developed based on the traditional defense in depth philosophy supported by deterministic and overly conservative methods for safety analysis. In the 1970s [1], conservative hypotheses were introduced for safety analyses to address existing uncertainties. Since then, intensive thermal-hydraulic experimental research has resulted in a considerable increase in knowledge and consequently in the development of best-estimate codes able to provide more realistic information about the physical behaviour and to identify the most relevant safety issues allowing the evaluation of the existing actual margins between the results of the calculations and the acceptance criteria. However, the best-estimate calculation results from complex thermal-hydraulic system codes (like Relap5, Cathare, Athlet, Trace, etc..) are affected by unavoidable approximations that are un-predictable without the use of computational tools that account for the various sources of uncertainty. Therefore the use of best-estimate codes (BE) within the reactor technology, either for design or safety purposes, implies understanding and accepting the limitations and the deficiencies of those codes. Taking into consideration the above framework, a comprehensive approach for utilizing quantified uncertainties arising from Integral Test Facilities (ITFs, [2]) and Separate Effect Test Facilities (SETFs, [3]) in the process of calibrating complex computer models for the application to NPP transient scenarios has been developed. The methodology proposed is capable of accommodating multiple SETFs and ITFs to learn as much as possible about uncertain parameters, allowing for the improvement of the computer model predictions based on the available experimental evidences. The proposed methodology constitutes a major step forward with respect to the generally used expert judgment and statistical methods as it permits a) to establish the uncertainties of any parameter
Visualizing uncertainties in a storm surge ensemble data assimilation and forecasting system
Hollt, Thomas
2015-01-15
We present a novel integrated visualization system that enables the interactive visual analysis of ensemble simulations and estimates of the sea surface height and other model variables that are used for storm surge prediction. Coastal inundation, caused by hurricanes and tropical storms, poses large risks for today\\'s societies. High-fidelity numerical models of water levels driven by hurricane-force winds are required to predict these events, posing a challenging computational problem, and even though computational models continue to improve, uncertainties in storm surge forecasts are inevitable. Today, this uncertainty is often exposed to the user by running the simulation many times with different parameters or inputs following a Monte-Carlo framework in which uncertainties are represented as stochastic quantities. This results in multidimensional, multivariate and multivalued data, so-called ensemble data. While the resulting datasets are very comprehensive, they are also huge in size and thus hard to visualize and interpret. In this paper, we tackle this problem by means of an interactive and integrated visual analysis system. By harnessing the power of modern graphics processing units for visualization as well as computation, our system allows the user to browse through the simulation ensembles in real time, view specific parameter settings or simulation models and move between different spatial and temporal regions without delay. In addition, our system provides advanced visualizations to highlight the uncertainty or show the complete distribution of the simulations at user-defined positions over the complete time series of the prediction. We highlight the benefits of our system by presenting its application in a real-world scenario using a simulation of Hurricane Ike.
International Nuclear Information System (INIS)
Heo, Jaeseok; Kim, Kyung Doo
2015-01-01
Statistical approaches to uncertainty quantification and sensitivity analysis are very important in estimating the safety margins for an engineering design application. This paper presents a system analysis and optimization toolkit developed by Korea Atomic Energy Research Institute (KAERI), which includes multiple packages of the sensitivity analysis and uncertainty quantification algorithms. In order to reduce the computing demand, multiple compute resources including multiprocessor computers and a network of workstations are simultaneously used. A Graphical User Interface (GUI) was also developed within the parallel computing framework for users to readily employ the toolkit for an engineering design and optimization problem. The goal of this work is to develop a GUI framework for engineering design and scientific analysis problems by implementing multiple packages of system analysis methods in the parallel computing toolkit. This was done by building an interface between an engineering simulation code and the system analysis software packages. The methods and strategies in the framework were designed to exploit parallel computing resources such as those found in a desktop multiprocessor workstation or a network of workstations. Available approaches in the framework include statistical and mathematical algorithms for use in science and engineering design problems. Currently the toolkit has 6 modules of the system analysis methodologies: deterministic and probabilistic approaches of data assimilation, uncertainty propagation, Chi-square linearity test, sensitivity analysis, and FFTBM
Energy Technology Data Exchange (ETDEWEB)
Heo, Jaeseok; Kim, Kyung Doo [KAERI, Daejeon (Korea, Republic of)
2015-05-15
Statistical approaches to uncertainty quantification and sensitivity analysis are very important in estimating the safety margins for an engineering design application. This paper presents a system analysis and optimization toolkit developed by Korea Atomic Energy Research Institute (KAERI), which includes multiple packages of the sensitivity analysis and uncertainty quantification algorithms. In order to reduce the computing demand, multiple compute resources including multiprocessor computers and a network of workstations are simultaneously used. A Graphical User Interface (GUI) was also developed within the parallel computing framework for users to readily employ the toolkit for an engineering design and optimization problem. The goal of this work is to develop a GUI framework for engineering design and scientific analysis problems by implementing multiple packages of system analysis methods in the parallel computing toolkit. This was done by building an interface between an engineering simulation code and the system analysis software packages. The methods and strategies in the framework were designed to exploit parallel computing resources such as those found in a desktop multiprocessor workstation or a network of workstations. Available approaches in the framework include statistical and mathematical algorithms for use in science and engineering design problems. Currently the toolkit has 6 modules of the system analysis methodologies: deterministic and probabilistic approaches of data assimilation, uncertainty propagation, Chi-square linearity test, sensitivity analysis, and FFTBM.
Energy levels of one-dimensional systems satisfying the minimal length uncertainty relation
Energy Technology Data Exchange (ETDEWEB)
Bernardo, Reginald Christian S., E-mail: rcbernardo@nip.upd.edu.ph; Esguerra, Jose Perico H., E-mail: jesguerra@nip.upd.edu.ph
2016-10-15
The standard approach to calculating the energy levels for quantum systems satisfying the minimal length uncertainty relation is to solve an eigenvalue problem involving a fourth- or higher-order differential equation in quasiposition space. It is shown that the problem can be reformulated so that the energy levels of these systems can be obtained by solving only a second-order quasiposition eigenvalue equation. Through this formulation the energy levels are calculated for the following potentials: particle in a box, harmonic oscillator, Pöschl–Teller well, Gaussian well, and double-Gaussian well. For the particle in a box, the second-order quasiposition eigenvalue equation is a second-order differential equation with constant coefficients. For the harmonic oscillator, Pöschl–Teller well, Gaussian well, and double-Gaussian well, a method that involves using Wronskians has been used to solve the second-order quasiposition eigenvalue equation. It is observed for all of these quantum systems that the introduction of a nonzero minimal length uncertainty induces a positive shift in the energy levels. It is shown that the calculation of energy levels in systems satisfying the minimal length uncertainty relation is not limited to a small number of problems like particle in a box and the harmonic oscillator but can be extended to a wider class of problems involving potentials such as the Pöschl–Teller and Gaussian wells.
A new costing model in hospital management: time-driven activity-based costing system.
Öker, Figen; Özyapıcı, Hasan
2013-01-01
Traditional cost systems cause cost distortions because they cannot meet the requirements of today's businesses. Therefore, a new and more effective cost system is needed. Consequently, time-driven activity-based costing system has emerged. The unit cost of supplying capacity and the time needed to perform an activity are the only 2 factors considered by the system. Furthermore, this system determines unused capacity by considering practical capacity. The purpose of this article is to emphasize the efficiency of the time-driven activity-based costing system and to display how it can be applied in a health care institution. A case study was conducted in a private hospital in Cyprus. Interviews and direct observations were used to collect the data. The case study revealed that the cost of unused capacity is allocated to both open and laparoscopic (closed) surgeries. Thus, by using the time-driven activity-based costing system, managers should eliminate the cost of unused capacity so as to obtain better results. Based on the results of the study, hospital management is better able to understand the costs of different surgeries. In addition, managers can easily notice the cost of unused capacity and decide how many employees to be dismissed or directed to other productive areas.
International Nuclear Information System (INIS)
Handa, Himesh; Sharma, B.B.
2016-01-01
Highlights: • New adaptive control design strategy to address chaotic system synchronization in master-slave configuration. • To derive control structure using model reference adaptive control like approach. • Extension of results to address general case with known and unknown system parameters. • Application of proposed strategy to chaotic systems. - Abstract: In this paper, a new adaptive feedback control design technique for the synchronization of a class of chaotic systems in master–slave configuration is proposed. The controller parameters are assumed to be unknown and are evolved using adaptation laws so as to achieve synchronization. To replicate real system operation, uncertainties are considered in both master as well as salve system parameters and adaptation laws for uncertain parameters are analytically derived using Lyapunov stability theory. The proposed strategy is derived by mimicking model reference adaptive control like structure for synchronization problem. To validate the methodology, two Genesio–Tesi systems and two Rossler's Prototype-4 systems are considered in master–slave configuration for synchronization. The analysis is done first with known system parameters and then uncertainties in system parameters are considered. Finally, detailed simulation results are provided to illustrate the effectiveness of the proposed results.
Adams, Vanessa M.; Segan, Daniel B.; Pressey, Robert L.
2011-01-01
Many governments have recently gone on record promising large-scale expansions of protected areas to meet global commitments such as the Convention on Biological Diversity. As systems of protected areas are expanded to be more comprehensive, they are more likely to be implemented if planners have realistic budget estimates so that appropriate funding can be requested. Estimating financial budgets a priori must acknowledge the inherent uncertainties and assumptions associated with key parameters, so planners should recognize these uncertainties by estimating ranges of potential costs. We explore the challenge of budgeting a priori for protected area expansion in the face of uncertainty, specifically considering the future expansion of protected areas in Queensland, Australia. The government has committed to adding ∼12 million ha to the reserve system, bringing the total area protected to 20 million ha by 2020. We used Marxan to estimate the costs of potential reserve designs with data on actual land value, market value, transaction costs, and land tenure. With scenarios, we explored three sources of budget variability: size of biodiversity objectives; subdivision of properties; and legal acquisition routes varying with tenure. Depending on the assumptions made, our budget estimates ranged from $214 million to $2.9 billion. Estimates were most sensitive to assumptions made about legal acquisition routes for leasehold land. Unexpected costs (costs encountered by planners when real-world costs deviate from assumed costs) responded non-linearly to inability to subdivide and percentage purchase of private land. A financially conservative approach - one that safeguards against large cost increases while allowing for potential financial windfalls - would involve less optimistic assumptions about acquisition and subdivision to allow Marxan to avoid expensive properties where possible while meeting conservation objectives. We demonstrate how a rigorous analysis can inform
Verification and uncertainty evaluation of CASMO-3/MASTER nuclear analysis system
Energy Technology Data Exchange (ETDEWEB)
Song, Jae Seung; Cho, Byung Oh; Joo, Han Kyu; Zee, Sung Quun; Lee, Chung Chan; Park, Sang Yoon
2000-06-01
MASTER is a nuclear design code developed by KAERI. It uses group constants generated by CASMO-3 developed by Studsvik. In this report the verification and evaluation of uncertainty were performed for the code system application in nuclear reactor core analysis and design. The verification is performed via various benchmark comparisons for static and transient core condition, and core follow calculations with startup physics test predictions of total 14 cycles of pressurized water reactors. Benchmark calculation include comparisons with reference solutions of IAEA and OECA/NEA problems and critical experiment measurements. The uncertainty evaluation is focused to safety related parameters such as power distribution, reactivity coefficients, control rod worth and core reactivity. It is concluded that CASMO-3/MASTER can be applied for PWR core nuclear analysis and design without any bias factors. Also, it is verified that the system can be applied for SMART core, via supplemental comparisons with reference calculations by MCNP which is a probabilistic nuclear calculation code.
Verification and uncertainty evaluation of CASMO-3/MASTER nuclear analysis system
International Nuclear Information System (INIS)
Song, Jae Seung; Cho, Byung Oh; Joo, Han Kyu; Zee, Sung Quun; Lee, Chung Chan; Park, Sang Yoon
2000-06-01
MASTER is a nuclear design code developed by KAERI. It uses group constants generated by CASMO-3 developed by Studsvik. In this report the verification and evaluation of uncertainty were performed for the code system application in nuclear reactor core analysis and design. The verification is performed via various benchmark comparisons for static and transient core condition, and core follow calculations with startup physics test predictions of total 14 cycles of pressurized water reactors. Benchmark calculation include comparisons with reference solutions of IAEA and OECA/NEA problems and critical experiment measurements. The uncertainty evaluation is focused to safety related parameters such as power distribution, reactivity coefficients, control rod worth and core reactivity. It is concluded that CASMO-3/MASTER can be applied for PWR core nuclear analysis and design without any bias factors. Also, it is verified that the system can be applied for SMART core, via supplemental comparisons with reference calculations by MCNP which is a probabilistic nuclear calculation code
Bayesian Statistics and Uncertainty Quantification for Safety Boundary Analysis in Complex Systems
He, Yuning; Davies, Misty Dawn
2014-01-01
The analysis of a safety-critical system often requires detailed knowledge of safe regions and their highdimensional non-linear boundaries. We present a statistical approach to iteratively detect and characterize the boundaries, which are provided as parameterized shape candidates. Using methods from uncertainty quantification and active learning, we incrementally construct a statistical model from only few simulation runs and obtain statistically sound estimates of the shape parameters for safety boundaries.
Directory of Open Access Journals (Sweden)
Wang Mingjie
2017-01-01
Full Text Available A framework of non-intrusive polynomial chaos expansion method (PC was proposed to investigate the statistic characteristics of the response of structural-acoustic system containing random uncertainty. The PC method does not need to reformulate model equations, and the statistics of the response can be evaluated directly. The results show that compared to the direct Monte Carlo method (MCM based on the original numerical model, the PC method is effective and more efficient.
International Nuclear Information System (INIS)
Shindo, R.; Yamashita, K.; Murata, I.
1991-01-01
The nuclear design code system for the HTTR consists of one dimensional cell burnup computer code, developed in JAERI and the TWOTRAN-2 transport code. In order to satisfy related design criteria, uncertainty of the calculation was investigated by comparing the calculated and experimental results. The experiments were performed with a graphite moderated critical assembly. It was confirmed that discrepancies between calculations and experiments were small enough to be allowed in the nuclear design of HTTR. 8 refs, 6 figs
SWEPP PAN assay system uncertainty analysis: Passive mode measurements of graphite waste
International Nuclear Information System (INIS)
Blackwood, L.G.; Harker, Y.D.; Meachum, T.R.; Yoon, Woo Y.
1997-07-01
The Idaho National Engineering and Environmental Laboratory is being used as a temporary storage facility for transuranic waste generated by the U.S. Nuclear Weapons program at the Rocky Flats Plant (RFP) in Golden, Colorado. Currently, there is a large effort in progress to prepare to ship this waste to the Waste Isolation Pilot Plant (WIPP) in Carlsbad, New Mexico. In order to meet the TRU Waste Characterization Quality Assurance Program Plan nondestructive assay compliance requirements and quality assurance objectives, it is necessary to determine the total uncertainty of the radioassay results produced by the Stored Waste Examination Pilot Plant (SWEPP) Passive Active Neutron (PAN) radioassay system. To this end a modified statistical sampling and verification approach has been developed to determine the total uncertainty of a PAN measurement. In this approach the total performance of the PAN nondestructive assay system is simulated using computer models of the assay system and the resultant output is compared with the known input to assess the total uncertainty. This paper is one of a series of reports quantifying the results of the uncertainty analysis of the PAN system measurements for specific waste types and measurement modes. In particular this report covers passive mode measurements of weapons grade plutonium-contaminated graphite molds contained in 208 liter drums (waste code 300). The validity of the simulation approach is verified by comparing simulated output against results from measurements using known plutonium sources and a surrogate graphite waste form drum. For actual graphite waste form conditions, a set of 50 cases covering a statistical sampling of the conditions exhibited in graphite wastes was compiled using a Latin hypercube statistical sampling approach
A phantom-based study for assessing the error and uncertainty of a neuronavigation system
Natalia Izquierdo-Cifuentes; Genaro Daza-Santacoloma; Walter Serna-Serna
2017-01-01
This document describes a calibration protocol with the intention to introduce a guide to standardize the metrological vocabulary among manufacturers of image-guided surgery systems. Two stages were developed to measure the errors and estimate the uncertainty of a neuronavigator in different situations, on the first one it was determined a mechanical error on a virtual model of an acrylic phantom, on the second it was determined a coordinate error on the computerized axial tomography scan of ...
Energy Technology Data Exchange (ETDEWEB)
Knio, Omar [Duke Univ., Durham, NC (United States). Dept. of Mechanical Engineering and Materials Science
2017-05-05
The current project develops a novel approach that uses a probabilistic description to capture the current state of knowledge about the computational solution. To effectively spread the computational effort over multiple nodes, the global computational domain is split into many subdomains. Computational uncertainty in the solution translates into uncertain boundary conditions for the equation system to be solved on those subdomains, and many independent, concurrent subdomain simulations are used to account for this bound- ary condition uncertainty. By relying on the fact that solutions on neighboring subdomains must agree with each other, a more accurate estimate for the global solution can be achieved. Statistical approaches in this update process make it possible to account for the effect of system faults in the probabilistic description of the computational solution, and the associated uncertainty is reduced through successive iterations. By combining all of these elements, the probabilistic reformulation allows splitting the computational work over very many independent tasks for good scalability, while being robust to system faults.
Energy Technology Data Exchange (ETDEWEB)
Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jiam; Subbarao, Krishnappa [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
2010-07-01
An approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. An assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, incorporating sources of uncertainty - both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures). A new method called the ''flying-brick'' technique is developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an EMS system is developed. Demonstration through integration with an EMS system illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems from other vendors. (orig.)
Fuzzy Modeling and Synchronization of a New Hyperchaotic Complex System with Uncertainties
Directory of Open Access Journals (Sweden)
Hadi Delavari
2015-07-01
Full Text Available In this paper, the synchronization of a new hyperchaotic complex system based on T-S fuzzy model is proposed. First the considered hyperchaotic system is represented by T-S fuzzy model equivalently. Then by using the parallel distributed compensation (PDC method and by applying linear system theory and exact linearization (EL technique, a fuzzy controller is designed to realize the synchronization. Finally, simulation results are carried out to demonstrate the performance of our proposed control scheme, and also the robustness of the designed fuzzy controller to uncertainties.
Subsystem cost data for the tritium systems test assembly
International Nuclear Information System (INIS)
Bartlit, J.R.; Anderson, J.L.; Rexroth, V.G.
1983-01-01
Details of subsystem costs are among the questions most frequently asked about the $14.4 million Tritium Systems Test Assembly (TSTA) at Los Alamos National Laboratory. This paper presents a breakdown of cost components for each of the 20 major subsystems of TSTA. Also included are details to aid in adjusting the costs to other years, contracting conditions, or system sizes
International Nuclear Information System (INIS)
Wattanapongskorn, Naruemon; Coit, David W.
2007-01-01
In this paper, we model embedded system design and optimization, considering component redundancy and uncertainty in the component reliability estimates. The systems being studied consist of software embedded in associated hardware components. Very often, component reliability values are not known exactly. Therefore, for reliability analysis studies and system optimization, it is meaningful to consider component reliability estimates as random variables with associated estimation uncertainty. In this new research, the system design process is formulated as a multiple-objective optimization problem to maximize an estimate of system reliability, and also, to minimize the variance of the reliability estimate. The two objectives are combined by penalizing the variance for prospective solutions. The two most common fault-tolerant embedded system architectures, N-Version Programming and Recovery Block, are considered as strategies to improve system reliability by providing system redundancy. Four distinct models are presented to demonstrate the proposed optimization techniques with or without redundancy. For many design problems, multiple functionally equivalent software versions have failure correlation even if they have been independently developed. The failure correlation may result from faults in the software specification, faults from a voting algorithm, and/or related faults from any two software versions. Our approach considers this correlation in formulating practical optimization models. Genetic algorithms with a dynamic penalty function are applied in solving this optimization problem, and reasonable and interesting results are obtained and discussed
Directory of Open Access Journals (Sweden)
Adrian Nocoń
2015-09-01
Full Text Available This paper presents an analysis of the influence of uncertainty of power system mathematical model parameters on optimised parameters of PSS2A system stabilizers. Optimisation of power system stabilizer parameters was based on polyoptimisation (multi-criteria optimisation. Optimisation criteria were determined for disturbances occurring in a multi-machine power system, when taking into account transient waveforms associated with electromechanical swings (instantaneous power, angular speed and terminal voltage waveforms of generators. A genetic algorithm with floating-point encoding, tournament selection, mean crossover and perturbative mutations, modified for the needs of investigations, was used for optimisation. The impact of uncertainties on the quality of operation of power system stabilizers with optimised parameters has been evaluated using various deformation factors.
Recent evolutions in costing systems: A literature review of Time-Driven Activity-Based Costing
Siguenza Guzman, Lorena; Van den Abbeele, Alexandra; Vandewalle, Joos; Verhaaren, Henry; Cattrysse, Dirk
2013-01-01
This article provides a comprehensive literature review of Time-Driven Activity Based Costing (TDABC), a relatively new tool to improve the cost allocation to products and services. After a brief overview of traditional costing and activity based costing systems (ABC), a detailed description of the TDABC model is given and a comparison made between this methodology and its predecessor ABC. Thirty-six empirical contributions using TDABC over the period 2004-2012 were reviewed. The results and ...
Cost and performance analysis of physical security systems
International Nuclear Information System (INIS)
Hicks, M.J.; Yates, D.; Jago, W.H.; Phillips, A.W.
1998-04-01
Analysis of cost and performance of physical security systems can be a complex, multi-dimensional problem. There are a number of point tools that address various aspects of cost and performance analysis. Increased interest in cost tradeoffs of physical security alternatives has motivated development of an architecture called Cost and Performance Analysis (CPA), which takes a top-down approach to aligning cost and performance metrics. CPA incorporates results generated by existing physical security system performance analysis tools, and utilizes an existing cost analysis tool. The objective of this architecture is to offer comprehensive visualization of complex data to security analysts and decision-makers
Dynamic cost control information system for nuclear power plant construction
International Nuclear Information System (INIS)
Wang Yongqing; Liu Wei
1998-01-01
The authors first introduce the cost control functions of some overseas popular project management software at present and the specific ways of cost control of nuclear power plant construction in China. Then the authors stress the necessity of cost and schedule control integration and present the concept of dynamic cost control, the design scheme of dynamic cost control information system and the data structure modeling. Based on the above, the authors can develop the system which has the functions of dynamic estimate, cash flow management and cost optimization for nuclear engineering
International Nuclear Information System (INIS)
Mok, Chin Man; Doughty, Christine; Zhang, Keni; Pruess, Karsten; Kiureghian, Armen; Zhang, Miao; Kaback, Dawn
2010-01-01
A new computer code, CALRELTOUGH, which uses reliability methods to incorporate parameter sensitivity and uncertainty analysis into subsurface flow and transport models, was developed by Geomatrix Consultants, Inc. in collaboration with Lawrence Berkeley National Laboratory and University of California at Berkeley. The CALREL reliability code was developed at the University of California at Berkely for geotechnical applications and the TOUGH family of codes was developed at Lawrence Berkeley National Laboratory for subsurface flow and tranport applications. The integration of the two codes provides provides a new approach to deal with uncertainties in flow and transport modeling of the subsurface, such as those uncertainties associated with hydrogeology parameters, boundary conditions, and initial conditions of subsurface flow and transport using data from site characterization and monitoring for conditioning. The new code enables computation of the reliability of a system and the components that make up the system, instead of calculating the complete probability distributions of model predictions at all locations at all times. The new CALRELTOUGH code has tremendous potential to advance subsurface understanding for a variety of applications including subsurface energy storage, nuclear waste disposal, carbon sequestration, extraction of natural resources, and environmental remediation. The new code was tested on a carbon sequestration problem as part of the Phase I project. Phase iI was not awarded.
Uncertainty evaluation of a regional real-time system for rain-induced landslides
Kirschbaum, Dalia; Stanley, Thomas; Yatheendradas, Soni
2015-04-01
A new prototype regional model and evaluation framework has been developed over Central America and the Caribbean region using satellite-based information including precipitation estimates, modeled soil moisture, topography, soils, as well as regionally available datasets such as road networks and distance to fault zones. The algorithm framework incorporates three static variables: a susceptibility map; a 24-hr rainfall triggering threshold; and an antecedent soil moisture variable threshold, which have been calibrated using historic landslide events. The thresholds are regionally heterogeneous and are based on the percentile distribution of the rainfall or antecedent moisture time series. A simple decision tree algorithm framework integrates all three variables with the rainfall and soil moisture time series and generates a landslide nowcast in real-time based on the previous 24 hours over this region. This system has been evaluated using several available landslide inventories over the Central America and Caribbean region. Spatiotemporal uncertainty and evaluation metrics of the model are presented here based on available landslides reports. This work also presents a probabilistic representation of potential landslide activity over the region which can be used to further refine and improve the real-time landslide hazard assessment system as well as better identify and characterize the uncertainties inherent in this type of regional approach. The landslide algorithm provides a flexible framework to improve hazard estimation and reduce uncertainty at any spatial and temporal scale.
The role of models in managing the uncertainty of software-intensive systems
International Nuclear Information System (INIS)
Littlewood, Bev; Neil, Martin; Ostrolenk, Gary
1995-01-01
It is increasingly argued that uncertainty is an inescapable feature of the design and operational behaviour of software-intensive systems. This paper elaborates the role of models in managing such uncertainty, in relation to evidence and claims for dependability. Personal and group models are considered with regard to abstraction, consensus and corroboration. The paper focuses on the predictive property of models, arguing for the need for empirical validation of their trustworthiness through experimentation and observation. The impact on trustworthiness of human fallibility, formality of expression and expressiveness is discussed. The paper identifies two criteria for deciding the degree of trust to be placed in a model, and hence also for choosing between models, namely accuracy and informativeness. Finally, analogy and reuse are proposed as the only means by which empirical evidence can be established for models in software engineering
Schoute, M.; Budding, G.T.
2017-01-01
Purpose: This study examines whether changes in environmental and funding uncertainty during the first three years after the outbreak of the global financial crisis (which we presume to have increased significantly) are associated with changes in cost system design and intensity of use.
Abu, M. Y.; Nor, E. E. Mohd; Rahman, M. S. Abd
2018-04-01
Integration between quality and costing system is very crucial in order to achieve an accurate product cost and profit. Current practice by most of remanufacturers, there are still lacking on optimization during the remanufacturing process which contributed to incorrect variables consideration to the costing system. Meanwhile, traditional costing accounting being practice has distortion in the cost unit which lead to inaccurate cost of product. The aim of this work is to identify the critical and non-critical variables during remanufacturing process using Mahalanobis-Taguchi System and simultaneously estimate the cost using Activity Based Costing method. The orthogonal array was applied to indicate the contribution of variables in the factorial effect graph and the critical variables were considered with overhead costs that are actually demanding the activities. This work improved the quality inspection together with costing system to produce an accurate profitability information. As a result, the cost per unit of remanufactured crankshaft of MAN engine model with 5 critical crankpins is MYR609.50 while Detroit engine model with 4 critical crankpins is MYR1254.80. The significant of output demonstrated through promoting green by reducing re-melting process of damaged parts to ensure consistent benefit of return cores.
Impacts of intermittent renewable generation on electricity system costs
International Nuclear Information System (INIS)
Batalla-Bejerano, Joan; Trujillo-Baute, Elisa
2016-01-01
A successful deployment of power generation coming from variable renewable sources, such as wind and solar photovoltaic, strongly depends on the economic cost of system integration. This paper, in seeking to look beyond the impact of renewable generation on the evolution of the total economic costs associated with the operation of the electricity system, aims to estimate the sensitivity of balancing market requirements and costs to the variable and non-fully predictable nature of intermittent renewable generation. The estimations reported in this paper for the Spanish electricity system stress the importance of both attributes as well as power system flexibility when accounting for the cost of balancing services. - Highlights: •A successful deployment of VRES-E strongly depends on the economic cost of its integration. •We estimate the sensitivity of balancing market requirements and costs to VRES-E. •Integration costs depend on variability, predictability and system flexibility.
Anghileri, D.; Castelletti, A.; Burlando, P.
2016-12-01
European energy markets have experienced dramatic changes in the last years because of the massive introduction of Variable Renewable Sources (VRSs), such as wind and solar power sources, in the generation portfolios in many countries. VRSs i) are intermittent, i.e., their production is highly variable and only partially predictable, ii) are characterized by no correlation between production and demand, iii) have negligible costs of production, and iv) have been largely subsidized. These features result in lower energy prices, but, at the same time, in increased price volatility, and in network stability issues, which pose a threat to traditional power sources because of smaller incomes and higher maintenance costs associated to a more flexible operation of power systems. Storage hydropower systems play an important role in compensating production peaks, both in term of excess and shortage of energy. Traditionally, most of the research effort in hydropower reservoir operation has focused on modeling and forecasting reservoir inflow as well as designing reservoir operation accordingly. Nowadays, price variability may be the largest source of uncertainty in the context of hydropower systems, especially when considering medium-to-large reservoirs, whose storage can easily buffer small inflow fluctuations. In this work, we compare the effects of uncertain inflow and energy price forecasts on hydropower production and profitability. By adding noise to historic inflow and price trajectories, we build a set of synthetic forecasts corresponding to different levels of predictability and assess their impact on reservoir operating policies and performances. The study is conducted on different hydropower systems, including storage systems and pumped-storage systems, with different characteristics, e.g., different inflow-capacity ratios. The analysis focuses on Alpine hydropower systems where the hydrological regime ranges from purely ice and snow-melt dominated to mixed snow
Supporting qualified database for V and V and uncertainty evaluation of best-estimate system codes
International Nuclear Information System (INIS)
Petruzzi, A.; D'Auria, F.
2014-01-01
Uncertainty evaluation constitutes a key feature of BEPU (Best Estimate Plus Uncertainty) process. The uncertainty can be the result of a Monte Carlo type analysis involving input uncertainty parameters or the outcome of a process involving the use of experimental data and connected code calculations. Those uncertainty methods are discussed in several papers and guidelines (IAEA-SRS- 52, OECD/NEA BEMUSE reports). The present paper aims at discussing the role and the depth of the analysis required for merging from one side suitable experimental data and on the other side qualified code calculation results. This aspect is mostly connected with the second approach for uncertainty mentioned above, but it can be used also in the framework of the first approach. Namely, the paper discusses the features and structure of the database that includes the following kinds of documents: 1. The' RDS-facility' (Reference Data Set for the selected facility): this includes the description of the facility, the geometrical characterization of any component of the facility, the instrumentations, the data acquisition system, the evaluation of pressure losses, the physical properties of the material and the characterization of pumps, valves and heat losses; 2. The 'RDS-test' (Reference Data Set for the selected test of the facility): this includes the description of the main phenomena investigated during the test, the configuration of the facility for the selected test (possible new evaluation of pressure and heat losses if needed) and the specific boundary and initial conditions; 3. The 'QP' (Qualification Report) of the code calculation results: this includes the description of the nodalization developed following a set of homogeneous techniques, the achievement of the steady state conditions and the qualitative and quantitative analysis of the transient with the characterization of the Relevant Thermal-Hydraulics Aspects (RTA); 4. The EH (Engineering
Automated cost modeling for coal combustion systems
International Nuclear Information System (INIS)
Rowe, R.M.; Anast, K.R.
1991-01-01
This paper reports on cost information developed at AMAX R and D Center for coal-water slurry production implemented in an automated spreadsheet (Lotus 123) for personal computer use. The spreadsheet format allows the user toe valuate impacts of various process options, coal feedstock characteristics, fuel characteristics, plant location sites, and plant sizes on fuel cost. Model flexibility reduces time and labor required to determine fuel costs and provides a basis to compare fuels manufactured by different processes. The model input includes coal characteristics, plant flowsheet definition, plant size, and market location. Based on these inputs, selected unit operations are chosen for coal processing
Khan, Sobia; Vandermorris, Ashley; Shepherd, John; Begun, James W; Lanham, Holly Jordan; Uhl-Bien, Mary; Berta, Whitney
2018-03-21
Complexity thinking is increasingly being embraced in healthcare, which is often described as a complex adaptive system (CAS). Applying CAS to healthcare as an explanatory model for understanding the nature of the system, and to stimulate changes and transformations within the system, is valuable. A seminar series on systems and complexity thinking hosted at the University of Toronto in 2016 offered a number of insights on applications of CAS perspectives to healthcare that we explore here. We synthesized topics from this series into a set of six insights on how complexity thinking fosters a deeper understanding of accepted ideas in healthcare, applications of CAS to actors within the system, and paradoxes in applications of complexity thinking that may require further debate: 1) a complexity lens helps us better understand the nebulous term "context"; 2) concepts of CAS may be applied differently when actors are cognizant of the system in which they operate; 3) actor responses to uncertainty within a CAS is a mechanism for emergent and intentional adaptation; 4) acknowledging complexity supports patient-centred intersectional approaches to patient care; 5) complexity perspectives can support ways that leaders manage change (and transformation) in healthcare; and 6) complexity demands different ways of implementing ideas and assessing the system. To enhance our exploration of key insights, we augmented the knowledge gleaned from the series with key articles on complexity in the literature. Ultimately, complexity thinking acknowledges the "messiness" that we seek to control in healthcare and encourages us to embrace it. This means seeing challenges as opportunities for adaptation, stimulating innovative solutions to ensure positive adaptation, leveraging the social system to enable ideas to emerge and spread across the system, and even more important, acknowledging that these adaptive actions are part of system behaviour just as much as periods of stability are. By
Evaluation of mechanical precision and alignment uncertainties for an integrated CT/LINAC system
International Nuclear Information System (INIS)
Court, Laurence; Rosen, Isaac; Mohan, Radhe; Dong Lei
2003-01-01
A new integrated CT/LINAC combination, in which the CT scanner is inside the radiation therapy treatment room and the same patient couch is used for CT scanning and treatment (after a 180-degree couch rotation), should allow for accurate correction of interfractional setup errors. The purpose of this study was to evaluate the sources of uncertainties, and to measure the overall precision of this system. The following sources of uncertainty were identified: (1) the patient couch position on the LINAC side after a rotation, (2) the patient couch position on the CT side after a rotation, (3) the patient couch position as indicated by its digital readout, (4) the difference in couch sag between the CT and LINAC positions, (5) the precision of the CT coordinates, (6) the identification of fiducial markers from CT images, (7) the alignment of contours with structures in the CT images, and (8) the alignment with setup lasers. The largest single uncertainties (one standard deviation or 1 SD) were found in couch position on the CT side after a rotation (0.5 mm in the RL direction) and the alignment of contours with the CT images (0.4 mm in the SI direction). All other sources of uncertainty are less than 0.3 mm (1 SD). The overall precision of two setup protocols was investigated in a controlled phantom study. A protocol that relies heavily on the mechanical integrity of the system, and assumes a fixed relationship between the LINAC isocenter and the CT images, gave a predicted precision (1 SD) of 0.6, 0.7, and 0.6 mm in the SI, RL and AP directions, respectively. The second protocol reduces reliance on the mechanical precision of the total system, particularly the patient couch, by using radio-opaque fiducial markers to transfer the isocenter information from the LINAC side to the CT images. This protocol gave a slightly improved predicted precision of 0.5, 0.4, and 0.4 mm in the SI, RL and AP directions, respectively. The distribution of phantom position after CT
STANDARDIZED COSTS FOR WATER SUPPLY DISTRIBUTION SYSTEMS
Presented within the report are cost data for construction and operation/maintenance of domestic water distribution and transmission pipelines, domestic water pumping stations, and domestic water storage reservoirs. To allow comparison of new construction with rehabilitation of e...
Tian, Zhen; Yuan, Jingqi; Xu, Liang; Zhang, Xiang; Wang, Jingcheng
2018-05-25
As higher requirements are proposed for the load regulation and efficiency enhancement, the control performance of boiler-turbine systems has become much more important. In this paper, a novel robust control approach is proposed to improve the coordinated control performance for subcritical boiler-turbine units. To capture the key features of the boiler-turbine system, a nonlinear control-oriented model is established and validated with the history operation data of a 300 MW unit. To achieve system linearization and decoupling, an adaptive feedback linearization strategy is proposed, which could asymptotically eliminate the linearization error caused by the model uncertainties. Based on the linearized boiler-turbine system, a second-order sliding mode controller is designed with the super-twisting algorithm. Moreover, the closed-loop system is proved robustly stable with respect to uncertainties and disturbances. Simulation results are presented to illustrate the effectiveness of the proposed control scheme, which achieves excellent tracking performance, strong robustness and chattering reduction. Copyright © 2018. Published by Elsevier Ltd.
Uncertainty analysis of an integrated energy system based on information theory
International Nuclear Information System (INIS)
Fu, Xueqian; Sun, Hongbin; Guo, Qinglai; Pan, Zhaoguang; Xiong, Wen; Wang, Li
2017-01-01
Currently, a custom-designed configuration of different renewable technologies named the integrated energy system (IES) has become popular due to its high efficiency, benefiting from complementary multi-energy technologies. This paper proposes an information entropy approach to quantify uncertainty in an integrated energy system based on a stochastic model that drives a power system model derived from an actual network on Barry Island. Due to the complexity of co-behaviours between generators, a copula-based approach is utilized to articulate the dependency structure of the generator outputs with regard to such factors as weather conditions. Correlation coefficients and mutual information, which are effective for assessing the dependence relationships, are applied to judge whether the stochastic IES model is correct. The calculated information values can be used to analyse the impacts of the coupling of power and heat on power flows and heat flows, and this approach will be helpful for improving the operation of IES. - Highlights: • The paper explores uncertainty of an integrated energy system. • The dependent weather model is verified from the perspective of correlativity. • The IES model considers the dependence between power and heat. • The information theory helps analyse the complexity of IES operation. • The application of the model is studied using an operational system on Barry Island.
Uncertainty analyses of the countermeasures module of the program system UFOMOD
International Nuclear Information System (INIS)
Fischer, F.; Ehrhardt, J.; Burkart, K.
1989-10-01
This report refers to uncertainty analyses of the countermeasures submodule of the program system UFOMOD, version NE 87/1, whose important input parameters are linked with probability distributions derived from expert judgement. Uncertainty bands show how much variability exists, sensitivity measures determine what causes this variability in consequences. Results are presented as confidence bands of complementary cumulative frequency distributions (CCFDs) of individual acute organ doses (lung, bone marrow), individual risks (pulmonary and hematopoietic syndrome) and the corresponding number of early fatalities, partially as a function of distance from the site. In addition the ranked influence of the uncertain parameters on the different consequence types is shown. For the estimation of confidence bands a model parameter sample size of n=60 equal to 3 times the number of uncertain model parameters is chosen. For a reduced set of nine model parameters a sample size of n=50 is selected. A total of 20 uncertain parameters is considered. The most sensitive parameters of the countermeasures submodule of UFOMOD appeared to be the initial delay of emergency actions in a keyhole shaped area A and the fractions of the population evacuating area A spontaneously during the sheltering period or staying outdoors. Under the conditions of the source term the influence on the overall uncertainty in the consequence variables - individual acute organ doses, individual risks and early fatalities - of driving times to leave the evacuation area is small. (orig./HP) [de
Framework for the assessment of PEMS (Portable Emissions Measurement Systems) uncertainty.
Giechaskiel, Barouch; Clairotte, Michael; Valverde-Morales, Victor; Bonnel, Pierre; Kregar, Zlatko; Franco, Vicente; Dilara, Panagiota
2018-06-13
European regulation 2016/427 (the first package of the so-called Real-Driving Emissions (RDE) regulation) introduced on-road testing with Portable Emissions Measurement Systems (PEMS) to complement the chassis dynamometer laboratory (Type I) test for the type approval of light-duty vehicles in the European Union since September 2017. The Not-To-Exceed (NTE) limit for a pollutant is the Type I test limit multiplied by a conformity factor that includes a margin for the additional measurement uncertainty of PEMS relative to standard laboratory equipment. The variability of measured results related to RDE trip design, vehicle operating conditions, and data evaluation remain outside of the uncertainty margin. The margins have to be reviewed annually (recital 10 of regulation 2016/646). This paper lays out the framework used for the first review of the NO x margin, which is also applicable to future margin reviews. Based on experimental data received from the stakeholders of the RDE technical working group in 2017, two NO x margin scenarios of 0.24-0.43 were calculated, accounting for different assumptions of possible zero drift behaviour of the PEMS during the tests. The reduced uncertainty margin compared to the one foreseen for 2020 (0.5) reflects the technical improvement of PEMS over the past few years. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Uncertainty and sensitivity analyses of the complete program system UFOMOD and of selected submodels
International Nuclear Information System (INIS)
Fischer, F.; Ehrhardt, J.; Hasemann, I.
1990-09-01
Uncertainty and sensitivity studies with the program system UFOMOD have been performed since several years on a submodel basis to get a deeper insight into the propagation of parameter uncertainties through the different modules and to quantify their contribution to the confidence bands of the intermediate and final results of an accident consequence assessment. In a series of investigations with the atmospheric dispersion module, the models describing early protective actions, the models calculating short-term organ doses and the health effects model of the near range subsystem NE of UFOMOD, a great deal of experience has been gained with methods and evaluation techniques for uncertainty and sensitivity analyses. Especially the influence on results of different sampling techniques and sample sizes, parameter distributions and correlations could be quantified and the usefulness of sensitivity measures for the interpretation of results could be demonstrated. In each submodel investigation, the (5%, 95%)-confidende bounds of the complementary cumulative frequency distributions (CCFDs) of various consequence types (activity concentrations of I-131 and Cs-137, individual acute organ doses, individual risks of nonstochastic health effects, and the number of early deaths) were calculated. The corresponding sensitivity analyses for each of these endpoints led to a list of parameters contributing significantly to the variation of mean values and 99% - fractiles. The most important parameters were extracted and combined for the final overall analysis. (orig.) [de
Probabilistic Mass Growth Uncertainties
Plumer, Eric; Elliott, Darren
2013-01-01
Mass has been widely used as a variable input parameter for Cost Estimating Relationships (CER) for space systems. As these space systems progress from early concept studies and drawing boards to the launch pad, their masses tend to grow substantially, hence adversely affecting a primary input to most modeling CERs. Modeling and predicting mass uncertainty, based on historical and analogous data, is therefore critical and is an integral part of modeling cost risk. This paper presents the results of a NASA on-going effort to publish mass growth datasheet for adjusting single-point Technical Baseline Estimates (TBE) of masses of space instruments as well as spacecraft, for both earth orbiting and deep space missions at various stages of a project's lifecycle. This paper will also discusses the long term strategy of NASA Headquarters in publishing similar results, using a variety of cost driving metrics, on an annual basis. This paper provides quantitative results that show decreasing mass growth uncertainties as mass estimate maturity increases. This paper's analysis is based on historical data obtained from the NASA Cost Analysis Data Requirements (CADRe) database.
Need for Cost Optimization of Space Life Support Systems
Jones, Harry W.; Anderson, Grant
2017-01-01
As the nation plans manned missions that go far beyond Earth orbit to Mars, there is an urgent need for a robust, disciplined systems engineering methodology that can identify an optimized Environmental Control and Life Support (ECLSS) architecture for long duration deep space missions. But unlike the previously used Equivalent System Mass (ESM), the method must be inclusive of all driving parameters and emphasize the economic analysis of life support system design. The key parameter for this analysis is Life Cycle Cost (LCC). LCC takes into account the cost for development and qualification of the system, launch costs, operational costs, maintenance costs and all other relevant and associated costs. Additionally, an effective methodology must consider system technical performance, safety, reliability, maintainability, crew time, and other factors that could affect the overall merit of the life support system.
Directory of Open Access Journals (Sweden)
Sayyad Delshad Saleh
2010-01-01
Full Text Available Abstract We propose a fractional-order controller to stabilize unstable fractional-order open-loop systems with interval uncertainty whereas one does not need to change the poles of the closed-loop system in the proposed method. For this, we will use the robust stability theory of Fractional-Order Linear Time Invariant (FO-LTI systems. To determine the control parameters, one needs only a little knowledge about the plant and therefore, the proposed controller is a suitable choice in the control of interval nonlinear systems and especially in fractional-order chaotic systems. Finally numerical simulations are presented to show the effectiveness of the proposed controller.
Quantum scattering in one-dimensional systems satisfying the minimal length uncertainty relation
Energy Technology Data Exchange (ETDEWEB)
Bernardo, Reginald Christian S., E-mail: rcbernardo@nip.upd.edu.ph; Esguerra, Jose Perico H., E-mail: jesguerra@nip.upd.edu.ph
2016-12-15
In quantum gravity theories, when the scattering energy is comparable to the Planck energy the Heisenberg uncertainty principle breaks down and is replaced by the minimal length uncertainty relation. In this paper, the consequences of the minimal length uncertainty relation on one-dimensional quantum scattering are studied using an approach involving a recently proposed second-order differential equation. An exact analytical expression for the tunneling probability through a locally-periodic rectangular potential barrier system is obtained. Results show that the existence of a non-zero minimal length uncertainty tends to shift the resonant tunneling energies to the positive direction. Scattering through a locally-periodic potential composed of double-rectangular potential barriers shows that the first band of resonant tunneling energies widens for minimal length cases when the double-rectangular potential barrier is symmetric but narrows down when the double-rectangular potential barrier is asymmetric. A numerical solution which exploits the use of Wronskians is used to calculate the transmission probabilities through the Pöschl–Teller well, Gaussian barrier, and double-Gaussian barrier. Results show that the probability of passage through the Pöschl–Teller well and Gaussian barrier is smaller in the minimal length cases compared to the non-minimal length case. For the double-Gaussian barrier, the probability of passage for energies that are more positive than the resonant tunneling energy is larger in the minimal length cases compared to the non-minimal length case. The approach is exact and applicable to many types of scattering potential.
Cost and performance analysis of physical security systems
International Nuclear Information System (INIS)
Hicks, M.J.; Yates, D.; Jago, W.H.
1997-01-01
CPA - Cost and Performance Analysis - is a prototype integration of existing PC-based cost and performance analysis tools: ACEIT (Automated Cost Estimating Integrated Tools) and ASSESS (Analytic System and Software for Evaluating Safeguards and Security). ACE is an existing DOD PC-based tool that supports cost analysis over the full life cycle of a system; that is, the cost to procure, operate, maintain and retire the system and all of its components. ASSESS is an existing DOE PC-based tool for analysis of performance of physical protection systems. Through CPA, the cost and performance data are collected into Excel workbooks, making the data readily available to analysts and decision makers in both tabular and graphical formats and at both the system and subsystem levels. The structure of the cost spreadsheets incorporates an activity-based approach to cost estimation. Activity-based costing (ABC) is an accounting philosophy used by industry to trace direct and indirect costs to the products or services of a business unit. By tracing costs through security sensors and procedures and then mapping the contributions of the various sensors and procedures to system effectiveness, the CPA architecture can provide security managers with information critical for both operational and strategic decisions. The architecture, features and applications of the CPA prototype are presented. 5 refs., 3 figs
Climate system properties determining the social cost of carbon
International Nuclear Information System (INIS)
Otto, Alexander; Allen, Myles R; Todd, Benjamin J; Bowerman, Niel; Frame, David J
2013-01-01
The choice of an appropriate scientific target to guide global mitigation efforts is complicated by uncertainties in the temperature response to greenhouse gas emissions. Much climate policy discourse has been based on the equilibrium global mean temperature increase following a concentration stabilization scenario. This is determined by the equilibrium climate sensitivity (ECS) which, in many studies, shows persistent, fat-tailed uncertainty. However, for many purposes, the equilibrium response is less relevant than the transient response. Here, we show that one prominent policy variable, the social cost of carbon (SCC), is generally better constrained by the transient climate response (TCR) than by the ECS. Simple analytic expressions show the SCC to be directly proportional to the TCR under idealized assumptions when the rate at which we discount future damage equals 2.8%. Using ensemble simulations of a simple climate model we find that knowing the true value of the TCR can reduce the relative uncertainty in the SCC substantially more, up to a factor of 3, than knowing the ECS under typical discounting assumptions. We conclude that the TCR, which is better constrained by observations, less subject to fat-tailed uncertainty and more directly related to the SCC, is generally preferable to the ECS as a single proxy for the climate response in SCC calculations. (letter)
Climate system properties determining the social cost of carbon
Otto, Alexander; Todd, Benjamin J.; Bowerman, Niel; Frame, David J.; Allen, Myles R.
2013-06-01
The choice of an appropriate scientific target to guide global mitigation efforts is complicated by uncertainties in the temperature response to greenhouse gas emissions. Much climate policy discourse has been based on the equilibrium global mean temperature increase following a concentration stabilization scenario. This is determined by the equilibrium climate sensitivity (ECS) which, in many studies, shows persistent, fat-tailed uncertainty. However, for many purposes, the equilibrium response is less relevant than the transient response. Here, we show that one prominent policy variable, the social cost of carbon (SCC), is generally better constrained by the transient climate response (TCR) than by the ECS. Simple analytic expressions show the SCC to be directly proportional to the TCR under idealized assumptions when the rate at which we discount future damage equals 2.8%. Using ensemble simulations of a simple climate model we find that knowing the true value of the TCR can reduce the relative uncertainty in the SCC substantially more, up to a factor of 3, than knowing the ECS under typical discounting assumptions. We conclude that the TCR, which is better constrained by observations, less subject to fat-tailed uncertainty and more directly related to the SCC, is generally preferable to the ECS as a single proxy for the climate response in SCC calculations.
Cost analysis of energy storage systems for electric utility applications
Energy Technology Data Exchange (ETDEWEB)
Akhil, A. [Sandia National Lab., Albuquerque, NM (United States); Swaminathan, S.; Sen, R.K. [R.K. Sen & Associates, Inc., Bethesda, MD (United States)
1997-02-01
Under the sponsorship of the Department of Energy, Office of Utility Technologies, the Energy Storage System Analysis and Development Department at Sandia National Laboratories (SNL) conducted a cost analysis of energy storage systems for electric utility applications. The scope of the study included the analysis of costs for existing and planned battery, SMES, and flywheel energy storage systems. The analysis also identified the potential for cost reduction of key components.
Factors Associated with Photovoltaic System Costs (Topical Issues Brief)
Energy Technology Data Exchange (ETDEWEB)
Mortensen, J.
2001-06-12
A variety of factors can affect the cost of photovoltaic systems. This report analyses the relationship among such factors by using information entered into a voluntary registry of PV systems and performing regression analyses. The results showed statistically significant relationships between photovoltaic system cost and (a) grid connection, (b) installation year, (c) areas where the utility had entered into volume purchasing agreements.
Empirical study of ERP systems implementation costs in Swiss SMES
Equey, C.; Kusters, R.J.; Varone, S.; Montandon, N.; Cordeiro, J.; Felipe, J.
2008-01-01
Based on sparse literature investigating the cost of ERP systems implementation, our research uses data from a survey of Swiss SMEs having implemented ERP in order to test cost drivers. The main innovation is the proposition of a new classification of cost drivers that depend on the enterprise
On Modeling and Analyzing Cost Factors in Information Systems Engineering
Mutschler, B.B.; Reichert, M.U.
Introducing enterprise information systems (EIS) is usually associated with high costs. It is therefore crucial to understand those factors that determine or influence these costs. Though software cost estimation has received considerable attention during the last decades, it is difficult to apply
The cost system of GSI - heavy ion facility in Darmstadt
International Nuclear Information System (INIS)
1979-01-01
The paper gives an overview about the organization and the research program of the GSI (Heavy Ion Facility in Darmstadt). The cost accounting system is discussed in detail, financing, cost center accounting and cost unit accounting are described. (A.N.)
Is the system really the solution? Operating costs in hospital systems.
Burns, Lawton Robert; McCullough, Jeffrey S; Wholey, Douglas R; Kruse, Gregory; Kralovec, Peter; Muller, Ralph
2015-06-01
Hospital system formation has recently accelerated. Executives emphasize scale economies that lower operating costs, a claim unsupported in academic research. Do systems achieve lower costs than freestanding facilities, and, if so, which system types? We test hypotheses about the relationship of cost with membership in systems, larger systems, and centralized and local hub-and-spoke systems. We also test whether these relationships have changed over time. Examining 4,000 U.S. hospitals during 1998 to 2010, we find no evidence that system members exhibit lower costs. However, members of smaller systems are lower cost than larger systems, and hospitals in centralized systems are lower cost than everyone else. There is no evidence that the system's spatial configuration is associated with cost, although national system hospitals exhibit higher costs. Finally, these results hold over time. We conclude that while systems in general may not be the solution to lower costs, some types of systems are. © The Author(s) 2015.
Cost analysis of seawater uranium recovered by a polymeric adsorbent system
International Nuclear Information System (INIS)
Schneider, E.; Lindner, H.; Sachde, D.; Flicker, M.
2014-01-01
In tandem with its adsorbent development and marine testing efforts, the United States Department of Energy, Office of Nuclear Energy, routinely updates and expands its cost analysis of technologies for extracting uranium from seawater. If informed by repeatable data from field tests, a rigorous cost analysis can convincingly establish seawater uranium as a “backstop” to conventional uranium resources. A backstop provides an essentially unlimited supply of an otherwise exhaustible resource. Its role is to remove the uncertainty around the long-term sustainability of the resource. The cost analysis ultimately aims to demonstrate a uranium production cost that is sustainable for the nuclear power industry, with no insurmountable technical or environmental roadblocks. It is also a tool for guiding further R&D, identifying inputs and performance factors where further development would offer the greatest reduction in costs and/or uncertainties. A life cycle discounted cash flow methodology is used to calculate the uranium production cost and its uncertainty from the costs of fundamental inputs including chemicals and materials, labor, equipment, energy carriers and facilities. The inputs themselves are defined by process flow models of the adsorbent fabrication and grafting, mooring at sea, recovery, and elution and purification steps in the seawater uranium recovery process. Pacific Northwest National Laboratory (PNNL) has carried out marine tests of the Oak Ridge National Laboratory amidoxime grafted polymer adsorbent in natural seawater. Multiple test campaigns demonstrated that after 60 days of immersion the uranium uptake averaged 3090 ± 310 μg U/g of adsorbent. Past ocean experiments on similar material by the Japan Atomic Energy Agency (JAEA) demonstrated that the adsorbent may be used in the sea six times before being replaced, with 5% uptake degradation per reuse. The mooring and recovery system envisioned for the adsorbent is similar to one proposed by
A fuzzy-stochastic power system planning model: Reflection of dual objectives and dual uncertainties
International Nuclear Information System (INIS)
Zhang, X.Y.; Huang, G.H.; Zhu, H.; Li, Y.P.
2017-01-01
In this study, a fuzzy stochastic dynamic fractional programming (FSDFP) method is proposed for supporting sustainable management of electric power system (EPS) under dual uncertainties. As an improvement upon the mixed-integer linear fractional programming, FSDFP can not only tackle multi-objective issues effectively without setting weights, but also can deal with uncertain parameters which have both stochastic and fuzzy characteristics. Thus, the developed method can help provide valuable information for supporting capacity-expansion planning and in-depth policy analysis of EPS management problems. For demonstrating these advantages, FSDFP has been applied to a case study of a typical regional EPS planning, where the decision makers have to deal with conflicts between economic development that maximizes the system profit and environmental protection that minimizes the carbon dioxide emissions. The obtained results can be analyzed to generate several decision alternatives, and can then help decision makers make suitable decisions under different input scenarios. Furthermore, comparisons of the solution from FSDFP method with that from fuzzy stochastic dynamic linear programming, linear fractional programming and dynamic stochastic fractional programming methods are undertaken. The contrastive analysis reveals that FSDFP is a more effective approach that can better characterize the complexities and uncertainties of real EPS management problems. - Highlights: • A fuzzy stochastic dynamic fractional programming (FSDFP) method is proposed. • FSDFP can address multiple conflicting objectives without setting weights. • FSDFP can reflect dual uncertainties with both stochastic and fuzzy characteristics. • Some reasonable solutions for a case of power system sustainable planning are generated. • Comparisons of the solutions from FSDFP with other optimization methods are undertaken.
System Approach of Logistic Costs Optimization Solution in Supply Chain
Majerčák, Peter; Masárová, Gabriela; Buc, Daniel; Majerčáková, Eva
2013-01-01
This paper is focused on the possibility of using the costs simulation in supply chain, which are on relative high level. Our goal is to determine the costs using logistic costs optimization which must necessarily be used in business activities in the supply chain management. The paper emphasizes the need to perform not isolated optimization in the whole supply chain. Our goal is to compare classic approach, when every part tracks its costs isolated, a try to minimize them, with the system (l...
Uncertainty evaluatins of CASMO-3/MASTER system for PWR core neutronics calculations
International Nuclear Information System (INIS)
Song, Jae Seung; Kim, Kang Seog; Lee, Kibog; Park, Jin Ha; Zee, Sung Quun
1996-01-01
Uncertainties in core neutronic calculations of CASMO-3/MASTER, which is a KAERI developed core nuclear design code system, were evaluated via comparisons with measured data. Comparisons were performed with plant measurement data from one Westinghouse type and one ABB-CE type plant and two Korean standard type plants. The CASMO-3/MASTER capability and levels of accuracy are concluded to be sufficient for the neutronics design including safety related parameters related with reactivity, power distributions, temperature and power coefficients, inverse boron worth and control bank worth
Mental health services costs within the Alberta criminal justice system.
Jacobs, Philip; Moffatt, Jessica; Dewa, Carolyn S; Nguyen, Thanh; Zhang, Ting; Lesage, Alain
2016-01-01
Mental illness has been widely cited as a driver of costs in the criminal justice system. The objective of this paper is to estimate the additional mental health service costs incurred within the criminal justice system that are incurred because of people with mental illnesses who go through the system. Our focus is on costs in Alberta. We set up a model of the flow of all persons through the criminal justice system, including police, court, and corrections components, and for mental health diversion, review, and forensic services. We estimate the transitional probabilities and costs that accrue as persons who have been charged move through the system. Costs are estimated for the Alberta criminal justice system as a whole, and for the mental illness component. Public expenditures for each person diverted or charged in Alberta in the criminal justice system, including mental health costs, were $16,138. The 95% range of this estimate was from $14,530 to $19,580. Of these costs, 87% were for criminal justice services and 13% were for mental illness-related services. Hospitalization for people with mental illness who were reviewed represented the greatest additional cost associated with mental illnesses. Treatment costs stemming from mental illnesses directly add about 13% onto those in the criminal justice system. Copyright © 2016 Elsevier Ltd. All rights reserved.
Steuten, Lotte Maria Gertruda; Vallejo-Torres, Laura; Bastide, Philippe; Buxton, Martin J.
2009-01-01
This paper presents a relatively simple cost model comparing the costs of using a commercial fibrin sealant (QUIXIL®) in addition to conventional haemostatic treatment vs. conventional treatment alone in total knee replacement (TKR) surgery, and demonstrates and discusses how one- and two-way
Cost-effectiveness of insulin analogs from the perspective of the Brazilian public health system
Directory of Open Access Journals (Sweden)
Maurílio de Souza Cazarim
2017-11-01
Full Text Available ABSTRACT Human insulin is provided by the Brazilian Public Health System (BPHS for the treatment of diabetes, however, legal proceedings to acquire insulin analogs have burdened the BPHS health system. The aim of this study was to perform a cost-effectiveness analysis to compare insulin analogs and human insulins. This is a pharmacoeconomic study of cost-effectiveness. The direct medical cost related to insulin extracted from the Ministry of Health drug price list was considered. The clinical results, i.e. reduction in glycated hemoglobin (HbA1c, were extracted by meta-analysis. Different scenarios were structured to measure the uncertainties regarding the costs and reduction in HbA1c. Decision tree was developed for sensitivity of Incremental Cost Effectiveness Ratio (ICER. A total of fifteen scenarios were structured. Given the best-case scenario for the insulin analogs, the insulins aspart, lispro, glargine and detemir showed an ICER of R$ 1,768.59; R$ 3,308.54; R$ 11,718.75 and R$ 2,685.22, respectively. In all scenarios in which the minimum effectiveness was proposed, lispro, glargine and detemir were dominant strategies. Sensitivity analysis showed that the aspart had R$ 3,066.98 [95 % CI: 2339.22; 4418.53] and detemir had R$ 6,163.97 [95% CI: 3919.29; 11401.57] for incremental costs. We concluded there was evidence that the insulin aspart is the most cost-effective.
Directory of Open Access Journals (Sweden)
Il Young Song
2015-01-01
Full Text Available This paper focuses on estimation of a nonlinear function of state vector (NFS in discrete-time linear systems with time-delays and model uncertainties. The NFS represents a multivariate nonlinear function of state variables, which can indicate useful information of a target system for control. The optimal nonlinear estimator of an NFS (in mean square sense represents a function of the receding horizon estimate and its error covariance. The proposed receding horizon filter represents the standard Kalman filter with time-delays and special initial horizon conditions described by the Lyapunov-like equations. In general case to calculate an optimal estimator of an NFS we propose using the unscented transformation. Important class of polynomial NFS is considered in detail. In the case of polynomial NFS an optimal estimator has a closed-form computational procedure. The subsequent application of the proposed receding horizon filter and nonlinear estimator to a linear stochastic system with time-delays and uncertainties demonstrates their effectiveness.
Testing low cost anaerobic digestion (AD) systems
To evaluate the potential for low technology and low cost digesters for small dairies, BARC and researchers from the University of Maryland installed six modified Taiwanese-model field-scale (FS) digesters near the original dairy manure digester. The FS units receive the same post-separated liquid ...
Managing social-ecological systems under uncertainty: implementation in the real world
Directory of Open Access Journals (Sweden)
Ana Nuno
2014-06-01
Full Text Available Management decisions for natural resources are not made in a vacuum; the environmental and ecological conditions as well as the socioeconomic and political contexts affect goals, the choice of interventions, their feasibility, and which outcomes are obtained. Although uncertainty is recognized as a feature of natural resource management, little attention has been given to the uncertainty generated by institutional settings, historical contingency, and individual people's influence. These implementation uncertainties, related to the translation of policy into practice, make it difficult to predict the outcomes of management interventions within social-ecological systems. Using the conservation of species hunted for bushmeat in the Serengeti as a case study, we investigated the challenges and potential barriers to successful implementation of natural resource management policies. We used a mixed-methods approach, combining semistructured interviews with scenario building, social network, and institutional analysis exercises. Using a management strategy evaluation (MSE conceptual framework, we obtained insights into the constraints and opportunities for fulfilling stakeholder aspirations for the social-ecological system, analyzed the multiple roles played by different institutions in the system, and described the interactions between different actor types. We found that the respondents had generally similar views about the current and future status of the Serengeti but disagreed about how to address issues of conservation concern and were more uncertain about the actual outcomes of management interventions. Improving conservation implementation (rather than research, monitoring, or status assessment was perceived as the key priority to be addressed. Institutional barriers were perceived as an important challenge given that the decision-making and implementation processes were broadly distributed across a number of institutions. Conservation social
Samad, Noor Asma Fazli Abdul; Sin, Gürkan; Gernaey, Krist V; Gani, Rafiqul
2013-11-01
This paper presents the application of uncertainty and sensitivity analysis as part of a systematic model-based process monitoring and control (PAT) system design framework for crystallization processes. For the uncertainty analysis, the Monte Carlo procedure is used to propagate input uncertainty, while for sensitivity analysis, global methods including the standardized regression coefficients (SRC) and Morris screening are used to identify the most significant parameters. The potassium dihydrogen phosphate (KDP) crystallization process is used as a case study, both in open-loop and closed-loop operation. In the uncertainty analysis, the impact on the predicted output of uncertain parameters related to the nucleation and the crystal growth model has been investigated for both a one- and two-dimensional crystal size distribution (CSD). The open-loop results show that the input uncertainties lead to significant uncertainties on the CSD, with appearance of a secondary peak due to secondary nucleation for both cases. The sensitivity analysis indicated that the most important parameters affecting the CSDs are nucleation order and growth order constants. In the proposed PAT system design (closed-loop), the target CSD variability was successfully reduced compared to the open-loop case, also when considering uncertainty in nucleation and crystal growth model parameters. The latter forms a strong indication of the robustness of the proposed PAT system design in achieving the target CSD and encourages its transfer to full-scale implementation. Copyright © 2013 Elsevier B.V. All rights reserved.
International Nuclear Information System (INIS)
Tanaka, Yohei; Momma, Akihiko; Kato, Ken; Negishi, Akira; Takano, Kiyonami; Nozaki, Ken; Kato, Tohru
2009-01-01
Uncertainty of electrical efficiency measurement was investigated for a 10 kW-class SOFC system using town gas. Uncertainty of heating value measured by the gas chromatography method on a mole base was estimated as ±0.12% at 95% level of confidence. Micro-gas chromatography with/without CH 4 quantification may be able to reduce uncertainty of measurement. Calibration and uncertainty estimation methods are proposed for flow-rate measurement of town gas with thermal mass-flow meters or controllers. By adequate calibrations for flowmeters, flow rate of town gas or natural gas at 35 standard litters per minute can be measured within relative uncertainty ±1.0% at 95 % level of confidence. Uncertainty of power measurement can be as low as ±0.14% when a precise wattmeter is used and calibrated properly. It is clarified that electrical efficiency for non-pressurized 10 kW-class SOFC systems can be measured within ±1.0% relative uncertainty at 95% level of confidence with the developed techniques when the SOFC systems are operated relatively stably
Cost of radon-barrier systems for uranium mill tailings
International Nuclear Information System (INIS)
Baker, E.G.; Hartley, J.N.
1982-08-01
This report deals specifically with the cost of three types of radon barrier systems, earthen covers, asphalt emulsion covers, and multilayer covers, which could meet standards proposed by the Environmental Protection Agency to stabilize uranium mill tailings located primarily in the western US. In addition, the report includes a sensitivity analysis of various factors which significantly effect the overall cost of the three systems. These analyses were based on a generic disposal site. Four different 3m thick earthen covers were tested and cost an average of $27/m 2 . The least expensive earthen cover cost was about $21/m 2 . The asphalt cover system (6 to 7 cm of asphalt topped with 0.6m of overburden) cost about $28/m 2 . The four multilayer covers averaged $57/m 2 , but materials handling problems encountered during the test inflated this cost above what was anticipated and significant cost reductions should be possible. The least expensive multilayer cover cost $43/m 2 . Based on the results of the Grand Junction field test we estimated the cost of covering the tailings from three high priority sites, Durango, Shiprock, and Salt Lake City (Vitro). The cost of a 3m earthen cover ranged from $18 to 33/m 2 for the seven disposal sites (two or three at each location) studied. The cost of asphalt cover systems were $23 to 28/m 2 and the multilayer cover costs were between $31 to 36/m 2 . The earthen cover costs are less than the Grand Junction field test cost primarily because cover material is available at or near most of the disposal sites selected. Earthen material was imported from 6 to 10 miles for the field test. Assuming more efficienct utilization of materials significantly reduced the cost of the multilayer covers
[Cost of therapy for neurodegenerative diseases. Applying an activity-based costing system].
Sánchez-Rebull, María-Victoria; Terceño Gómez, Antonio; Travé Bautista, Angeles
2013-01-01
To apply the activity based costing (ABC) model to calculate the cost of therapy for neurodegenerative disorders in order to improve hospital management and allocate resources more efficiently. We used the case study method in the Francolí long-term care day center. We applied all phases of an ABC system to quantify the cost of the activities developed in the center. We identified 60 activities; the information was collected in June 2009. The ABC system allowed us to calculate the average cost per patient with respect to the therapies received. The most costly and commonly applied technique was psycho-stimulation therapy. Focusing on this therapy and on others related to the admissions process could lead to significant cost savings. ABC costing is a viable method for costing activities and therapies in long-term day care centers because it can be adapted to their structure and standard practice. This type of costing allows the costs of each activity and therapy, or combination of therapies, to be determined and aids measures to improve management. Copyright © 2012 SESPAS. Published by Elsevier Espana. All rights reserved.
Entanglement criterion for tripartite systems based on local sum uncertainty relations
Akbari-Kourbolagh, Y.; Azhdargalam, M.
2018-04-01
We propose a sufficient criterion for the entanglement of tripartite systems based on local sum uncertainty relations for arbitrarily chosen observables of subsystems. This criterion generalizes the tighter criterion for bipartite systems introduced by Zhang et al. [C.-J. Zhang, H. Nha, Y.-S. Zhang, and G.-C. Guo, Phys. Rev. A 81, 012324 (2010), 10.1103/PhysRevA.81.012324] and can be used for both discrete- and continuous-variable systems. It enables us to detect the entanglement of quantum states without having a complete knowledge of them. Its utility is illustrated by some examples of three-qubit, qutrit-qutrit-qubit, and three-mode Gaussian states. It is found that, in comparison with other criteria, this criterion is able to detect some three-qubit bound entangled states more efficiently.
Space construction system analysis. Part 2: Cost and programmatics
Vonflue, F. W.; Cooper, W.
1980-01-01
Cost and programmatic elements of the space construction systems analysis study are discussed. The programmatic aspects of the ETVP program define a comprehensive plan for the development of a space platform, the construction system, and the space shuttle operations/logistics requirements. The cost analysis identified significant items of cost on ETVP development, ground, and flight segments, and detailed the items of space construction equipment and operations.
Using systems gaming to explore decision-making under uncertainty in natural hazard crises
McCaughey, Jamie W.; Finnigan, David
2017-04-01
Faced with uncertain scientific forecasts of a potential hazard, it is perhaps natural to wait and see. As we wait, uncertainties do decrease, but so do our options to minimise impacts of the hazard. This tradeoff is fundamental to preparing for natural hazards, yet difficult to communicate. Interactive systems gaming is one promising way forward. We are developing in-person interactive games, drawing on role-playing and other table-top scenario exercises in natural hazards, as well as on game-based modeling of complex systems. Our games model an unfolding natural hazard crisis (such as volcanic unrest or an approaching typhoon) as a complex social-physical system. Participants take on the roles of diverse stakeholder groups (including government, scientists, media, farmers, city residents, and others) with differing expertise, responsibilities, and priorities. Interactions among these groups play out in a context of decreasing scientific uncertainty and decreasing options for actions to reduce societal risk. Key design challenges are (1) to engage players without trivialising the real-world context; (2) to provide the right level of guidance for players to navigate the system; and (3) to enable players to face realistic tradeoffs and see realistic consequences of their choices, without feeling frustrated that the game is set up for them to fail. We will first prototype the games with general public and secondary-school participants, then adjust this for specialist groups working in disaster management. We will illustrate participatory systems gaming techniques in our presentation 'A toolkit of systems gaming techniques' in the companion EGU session EOS6: 'Perform! A platform to discuss art & science projects with live presentation'.
Extreme Cost Reductions with Multi-Megawatt Centralized Inverter Systems
Energy Technology Data Exchange (ETDEWEB)
Schwabe, Ulrich [Alencon LLC; Fishman, Oleg [Alencon LLC
2015-03-20
The objective of this project was to fully develop, demonstrate, and commercialize a new type of utility scale PV system. Based on patented technology, this includes the development of a truly centralized inverter system with capacities up to 100MW, and a high voltage, distributed harvesting approach. This system promises to greatly impact both the energy yield from large scale PV systems by reducing losses and increasing yield from mismatched arrays, as well as reduce overall system costs through very cost effective conversion and BOS cost reductions enabled by higher voltage operation.
18 CFR 301.7 - Average System Cost methodology functionalization.
2010-04-01
... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Average System Cost... REGULATORY COMMISSION, DEPARTMENT OF ENERGY REGULATIONS FOR FEDERAL POWER MARKETING ADMINISTRATIONS AVERAGE SYSTEM COST METHODOLOGY FOR SALES FROM UTILITIES TO BONNEVILLE POWER ADMINISTRATION UNDER NORTHWEST POWER...
Directory of Open Access Journals (Sweden)
Douglas Domingues Bueno
2008-01-01
Full Text Available This paper deals with the study of algorithms for robust active vibration control in flexible structures considering uncertainties in system parameters. It became an area of enormous interest, mainly due to the countless demands of optimal performance in mechanical systems as aircraft, aerospace, and automotive structures. An important and difficult problem for designing active vibration control is to get a representative dynamic model. Generally, this model can be obtained using finite element method (FEM or an identification method using experimental data. Actuators and sensors may affect the dynamics properties of the structure, for instance, electromechanical coupling of piezoelectric material must be considered in FEM formulation for flexible and lightly damping structure. The nonlinearities and uncertainties involved in these structures make it a difficult task, mainly for complex structures as spatial truss structures. On the other hand, by using an identification method, it is possible to obtain the dynamic model represented through a state space realization considering this coupling. This paper proposes an experimental methodology for vibration control in a 3D truss structure using PZT wafer stacks and a robust control algorithm solved by linear matrix inequalities.
Wang, S.; Huang, G. H.; Baetz, B. W.; Huang, W.
2015-11-01
This paper presents a polynomial chaos ensemble hydrologic prediction system (PCEHPS) for an efficient and robust uncertainty assessment of model parameters and predictions, in which possibilistic reasoning is infused into probabilistic parameter inference with simultaneous consideration of randomness and fuzziness. The PCEHPS is developed through a two-stage factorial polynomial chaos expansion (PCE) framework, which consists of an ensemble of PCEs to approximate the behavior of the hydrologic model, significantly speeding up the exhaustive sampling of the parameter space. Multiple hypothesis testing is then conducted to construct an ensemble of reduced-dimensionality PCEs with only the most influential terms, which is meaningful for achieving uncertainty reduction and further acceleration of parameter inference. The PCEHPS is applied to the Xiangxi River watershed in China to demonstrate its validity and applicability. A detailed comparison between the HYMOD hydrologic model, the ensemble of PCEs, and the ensemble of reduced PCEs is performed in terms of accuracy and efficiency. Results reveal temporal and spatial variations in parameter sensitivities due to the dynamic behavior of hydrologic systems, and the effects (magnitude and direction) of parametric interactions depending on different hydrological metrics. The case study demonstrates that the PCEHPS is capable not only of capturing both expert knowledge and probabilistic information in the calibration process, but also of implementing an acceleration of more than 10 times faster than the hydrologic model without compromising the predictive accuracy.
GPI-repetitive control for linear systems with parameter uncertainty / variation
Directory of Open Access Journals (Sweden)
John A. Cortés-Romero
2015-01-01
Full Text Available Robust repetitive control problems for uncertain linear systems have been considered by different approaches. This article proposes the use of Repetitive Control and Generalized Proportional Integral (GPI Control in a complementary fashion. The conditioning and coupling of these techniques has been done in a time discrete context. Repetitive control is a control technique, based on the internal model principle, which yields perfect asymptotic tracking and rejection of periodic signals. On the other hand, GPI control is established as a robust linear control system design technique that is able to reject structured time polynomial additive perturbation, in particular, parameter uncertainty that can be locally approximated by time polynomial signal. GPI control provides a suitable stability and robustness conditions for the proper Repetitive Control operation. A stability analysis is presented under the frequency response framework using plant samples for different parameter uncertainty conditions. We carry out some comparative stability analysis with other complementary control approaches that has been effective for this kind of task, enhancing a better robustness and an improved performance for the GPI case. Illustrative simulation examples are presented which validate the proposed approach.
Evolutionary systems biology of amino acid biosynthetic cost in yeast.
Directory of Open Access Journals (Sweden)
Michael D Barton
2010-08-01
Full Text Available Every protein has a biosynthetic cost to the cell based on the synthesis of its constituent amino acids. In order to optimise growth and reproduction, natural selection is expected, where possible, to favour the use of proteins whose constituents are cheaper to produce, as reduced biosynthetic cost may confer a fitness advantage to the organism. Quantifying the cost of amino acid biosynthesis presents challenges, since energetic requirements may change across different cellular and environmental conditions. We developed a systems biology approach to estimate the cost of amino acid synthesis based on genome-scale metabolic models and investigated the effects of the cost of amino acid synthesis on Saccharomyces cerevisiae gene expression and protein evolution. First, we used our two new and six previously reported measures of amino acid cost in conjunction with codon usage bias, tRNA gene number and atomic composition to identify which of these factors best predict transcript and protein levels. Second, we compared amino acid cost with rates of amino acid substitution across four species in the genus Saccharomyces. Regardless of which cost measure is used, amino acid biosynthetic cost is weakly associated with transcript and protein levels. In contrast, we find that biosynthetic cost and amino acid substitution rates show a negative correlation, but for only a subset of cost measures. In the economy of the yeast cell, we find that the cost of amino acid synthesis plays a limited role in shaping transcript and protein expression levels compared to that of translational optimisation. Biosynthetic cost does, however, appear to affect rates of amino acid evolution in Saccharomyces, suggesting that expensive amino acids may only be used when they have specific structural or functional roles in protein sequences. However, as there appears to be no single currency to compute the cost of amino acid synthesis across all cellular and environmental
Directory of Open Access Journals (Sweden)
Sanne Lemmens
2016-06-01
Full Text Available The potential of organic Rankine cycle (ORC systems is acknowledged by both considerable research and development efforts and an increasing number of applications. Most research aims at improving ORC systems through technical performance optimization of various cycle architectures and working fluids. The assessment and optimization of technical feasibility is at the core of ORC development. Nonetheless, economic feasibility is often decisive when it comes down to considering practical instalments, and therefore an increasing number of publications include an estimate of the costs of the designed ORC system. Various methods are used to estimate ORC costs but the resulting values are rarely discussed with respect to accuracy and validity. The aim of this paper is to provide insight into the methods used to estimate these costs and open the discussion about the interpretation of these results. A review of cost engineering practices shows there has been a long tradition of industrial cost estimation. Several techniques have been developed, but the expected accuracy range of the best techniques used in research varies between 10% and 30%. The quality of the estimates could be improved by establishing up-to-date correlations for the ORC industry in particular. Secondly, the rapidly growing ORC cost literature is briefly reviewed. A graph summarizing the estimated ORC investment costs displays a pattern of decreasing costs for increasing power output. Knowledge on the actual costs of real ORC modules and projects remains scarce. Finally, the investment costs of a known heat recovery ORC system are discussed and the methodologies and accuracies of several approaches are demonstrated using this case as benchmark. The best results are obtained with factorial estimation techniques such as the module costing technique, but the accuracies may diverge by up to +30%. Development of correlations and multiplication factors for ORC technology in particular is
Cost modelling of electricity-producing hot dry rock (HDR) geothermal systems in the United Kingdom
International Nuclear Information System (INIS)
Doherty, P.; Harrison, R.
1995-01-01
A detailed and comprehensive cost model for Hot Dry Rock (HDR) electricity producing systems has been developed in this study. The model takes account of the major aspects of the HDR system, parameterized in terms of the main physical and cost parameters of the resource and the utilization system. A doublet configuration is assumed, and the conceptual HDR system which is defined in the study is based upon the UK Department of Energy (DEn) HDR geothermal R and D programme. The model has been used to calculate the costs of HDR electricity for a UK defined base case which represents a consensus view of what might be achieved in Cornwall in the long term. At 14.2 p/kWh (1988 costs) this cost appears to be unacceptably high. A wide-ranging sensitivity study has also been carried out on the main resource, geometrical, and operational parameters of the HDR system centred around the UK base case. The sensitivity study shows the most important parameters to be thermal gradient and depth. The geometrical arrangement and the shape of the reservoir constitute major uncertainties in HDR systems. Their effect on temperature has a major influence on system performance, and therefore a range of theoretically possible geometries have been studied and the importance of geometrical effects on HDR electricity costs assessed. The most cost effective HDR arrangement in terms of optimized volumes and flow rates has been investigated for a world-wide range of thermal settings. The main conclusions from this study suggests that for HDR electricity to be economic, thermal gradients of 55 o C/km and above, well depths of 5 km or less, and production fluid temperatures of 210 o C and above are required. (UK)
External costs and taxes in heat supply systems
International Nuclear Information System (INIS)
Karlsson, Aasa; Gustavsson, Leif
2003-01-01
A systems approach was used to compare different heating systems from a consumer perspective. The whole energy system was considered from natural resources to the required energy services. District heating, electric heat pumps, electric boilers, natural-gas-, oil- or pellet-fired local boilers were considered when supplying heat to a detached house. The district heat production included wood-chip-fired and natural-gas-fired cogeneration plants. Electricity other than cogenerated electricity was produced in wood-chip- and natural-gas-fired stand-alone power plants. The analysis includes four tax scenarios, as well as the external cost of environmental and health damage arising from energy conversion emission based on the ExternE study of the European Commission. The most cost-efficient systems were the natural-gas and oil boiler systems, followed by the heat pump and district heating systems, when the external cost and taxes were excluded. When including the external costs of CO 2 emission, the wood-fuel-based systems were much more cost efficient than the fossil-fuel-based systems, also when CO 2 capture and storage were applied. The external costs are, however, highly uncertain. Taxes steer towards lowering energy use and lowering CO 2 emission if they are levied solely on all the fossil-fuel-related emission and fuel use in the systems. If consumer electricity and heat taxes are used, the taxes have an impact on the total cost, regardless of the fuel used, thereby benefiting fuel-based local heating systems. The heat pump systems were the least affected by taxes, due to their high energy efficiency. The electric boiler systems were the least cost-efficient systems, also when the external cost and taxes were included
Model-based verification method for solving the parameter uncertainty in the train control system
International Nuclear Information System (INIS)
Cheng, Ruijun; Zhou, Jin; Chen, Dewang; Song, Yongduan
2016-01-01
This paper presents a parameter analysis method to solve the parameter uncertainty problem for hybrid system and explore the correlation of key parameters for distributed control system. For improving the reusability of control model, the proposed approach provides the support for obtaining the constraint sets of all uncertain parameters in the abstract linear hybrid automata (LHA) model when satisfying the safety requirements of the train control system. Then, in order to solve the state space explosion problem, the online verification method is proposed to monitor the operating status of high-speed trains online because of the real-time property of the train control system. Furthermore, we construct the LHA formal models of train tracking model and movement authority (MA) generation process as cases to illustrate the effectiveness and efficiency of the proposed method. In the first case, we obtain the constraint sets of uncertain parameters to avoid collision between trains. In the second case, the correlation of position report cycle and MA generation cycle is analyzed under both the normal and the abnormal condition influenced by packet-loss factor. Finally, considering stochastic characterization of time distributions and real-time feature of moving block control system, the transient probabilities of wireless communication process are obtained by stochastic time petri nets. - Highlights: • We solve the parameters uncertainty problem by using model-based method. • We acquire the parameter constraint sets by verifying linear hybrid automata models. • Online verification algorithms are designed to monitor the high-speed trains. • We analyze the correlation of key parameters and uncritical parameters. • The transient probabilities are obtained by using reliability analysis.
Management of Uncertainty by Statistical Process Control and a Genetic Tuned Fuzzy System
Directory of Open Access Journals (Sweden)
Stephan Birle
2016-01-01
Full Text Available In food industry, bioprocesses like fermentation often are a crucial part of the manufacturing process and decisive for the final product quality. In general, they are characterized by highly nonlinear dynamics and uncertainties that make it difficult to control these processes by the use of traditional control techniques. In this context, fuzzy logic controllers offer quite a straightforward way to control processes that are affected by nonlinear behavior and uncertain process knowledge. However, in order to maintain process safety and product quality it is necessary to specify the controller performance and to tune the controller parameters. In this work, an approach is presented to establish an intelligent control system for oxidoreductive yeast propagation as a representative process biased by the aforementioned uncertainties. The presented approach is based on statistical process control and fuzzy logic feedback control. As the cognitive uncertainty among different experts about the limits that define the control performance as still acceptable may differ a lot, a data-driven design method is performed. Based upon a historic data pool statistical process corridors are derived for the controller inputs control error and change in control error. This approach follows the hypothesis that if the control performance criteria stay within predefined statistical boundaries, the final process state meets the required quality definition. In order to keep the process on its optimal growth trajectory (model based reference trajectory a fuzzy logic controller is used that alternates the process temperature. Additionally, in order to stay within the process corridors, a genetic algorithm was applied to tune the input and output fuzzy sets of a preliminarily parameterized fuzzy controller. The presented experimental results show that the genetic tuned fuzzy controller is able to keep the process within its allowed limits. The average absolute error to the
Scalable multi-objective control for large scale water resources systems under uncertainty
Giuliani, Matteo; Quinn, Julianne; Herman, Jonathan; Castelletti, Andrea; Reed, Patrick
2016-04-01
The use of mathematical models to support the optimal management of environmental systems is rapidly expanding over the last years due to advances in scientific knowledge of the natural processes, efficiency of the optimization techniques, and availability of computational resources. However, undergoing changes in climate and society introduce additional challenges for controlling these systems, ultimately motivating the emergence of complex models to explore key causal relationships and dependencies on uncontrolled sources of variability. In this work, we contribute a novel implementation of the evolutionary multi-objective direct policy search (EMODPS) method for controlling environmental systems under uncertainty. The proposed approach combines direct policy search (DPS) with hierarchical parallelization of multi-objective evolutionary algorithms (MOEAs) and offers a threefold advantage: the DPS simulation-based optimization can be combined with any simulation model and does not add any constraint on modeled information, allowing the use of exogenous information in conditioning the decisions. Moreover, the combination of DPS and MOEAs prompts the generation or Pareto approximate set of solutions for up to 10 objectives, thus overcoming the decision biases produced by cognitive myopia, where narrow or restrictive definitions of optimality strongly limit the discovery of decision relevant alternatives. Finally, the use of large-scale MOEAs parallelization improves the ability of the designed solutions in handling the uncertainty due to severe natural variability. The proposed approach is demonstrated on a challenging water resources management problem represented by the optimal control of a network of four multipurpose water reservoirs in the Red River basin (Vietnam). As part of the medium-long term energy and food security national strategy, four large reservoirs have been constructed on the Red River tributaries, which are mainly operated for hydropower
Determination of the components of uncertainty for a dosimetry system in radiation protection
International Nuclear Information System (INIS)
Lopez, F.; Cabral, T.S.; Peixoto, J.G.
2013-01-01
This work is about the theoretical calculation of uncertainties associated to the dosimetry of photons of a 137 Cs source that will be used in a Dosimetry Laboratory. In this case recognition of the influence quantities that provide most uncertainty and the right choice of resolution of auxiliary equipment to obtain the smallest uncertainties according to the laboratory. (author)
International Nuclear Information System (INIS)
Kalinich, D. A.; Wilson, M. L.
2001-01-01
Seepage into the repository drifts is an important factor in total-system performance. Uncertainty and spatial variability are considered in the seepage calculations. The base-case results show 13.6% of the waste packages (WPs) have seepage. For 5th percentile uncertainty, 4.5% of the WPs have seepage and the seepage flow decreased by a factor of 2. For 95th percentile uncertainty, 21.5% of the WPs have seepage and the seepage flow increased by a factor of 2. Ignoring spatial variability resulted in seepage on 100% of the WPs, with a factor of 3 increase in the seepage flow
EOS Operations Systems: EDOS Implemented Changes to Reduce Operations Costs
Cordier, Guy R.; Gomez-Rosa, Carlos; McLemore, Bruce D.
2007-01-01
The authors describe in this paper the progress achieved to-date with the reengineering of the Earth Observing System (EOS) Data and Operations System (EDOS), the experience gained in the process and the ensuing reduction of ground systems operations costs. The reengineering effort included a major methodology change, applying to an existing schedule driven system, a data-driven system approach.
Logistic Vehicle System Replacement Cost Estimate
National Research Council Canada - National Science Library
Stinson, Margaret
1998-01-01
The Logistics Vehicle System (LVS) was originally fielded from 1985-1989. Most of the LVS fleet will reach end-of-service life in 2005, therefore the goal of the Logistics Vehicle System Replacement (LVSR...
Robust Backstepping Control for Cold Rolling Main Drive System with Nonlinear Uncertainties
Directory of Open Access Journals (Sweden)
Xu Yang
2013-01-01
Full Text Available The nonlinear model of main drive system in cold rolling process, which considers the influence with parameter uncertainties such as clearance and variable friction coefficient, as well as external disturbance by roll eccentricity and variation of strip material quality, is built. By transformation, the lower triangular structure form of main drive system is obtained. The backstepping algorithm based on signal compensation is proposed to design a linear time-invariant (LTI robust controller, including a nominal controller and a robust compensator. A comparison with PI controller shows that the controller has better disturbance attenuation performance and tracking behaviors. Meanwhile, according to its LTI characteristic, the robust controller can be realized easily; therefore it is also appropriated to high speed dynamic rolling process.
Climate change in the framework of external costs of energy systems
International Nuclear Information System (INIS)
Mayerhofer, P.
1994-01-01
Due to the continuing controversies concerning external costs of energy systems, the Commission of the European Union and the US-Department of Energy initiated a common project, External Costs of Fuel Cycles. The purpose of this project is to develop methodologies for the assessment of site-specific external costs on a marginal basis using a damage-function approach. For the assessment of climate change itself physical models are available. Here, the PC-model IMAGE developed by RIVM has been used for the time period up to 2100. Beyond this year, the carbon cycle is modeled with a response function. For the derivation of damage costs, a linear relationship between the global temperature change and the damage costs has been assumed. Thus, damage costs in the range of 0.10 to 0.53 US-cents/kWh for a discount rate of 3% are assessed for typical German fossil energy systems. The highest uncertainties are attached to the discount rate, the range for the climate sensitivity, and the forms of the global warming damage function. These points also have the strongest influence on the results. Hence, future research should be directed to the further analysis of these points. 30 refs., 5 figs., 5 tabs
Optimization under Uncertainty
Lopez, Rafael H.
2016-01-06
The goal of this poster is to present the main approaches to optimization of engineering systems in the presence of uncertainties. We begin by giving an insight about robust optimization. Next, we detail how to deal with probabilistic constraints in optimization, the so called the reliability based design. Subsequently, we present the risk optimization approach, which includes the expected costs of failure in the objective function. After that the basic description of each approach is given, the projects developed by CORE are presented. Finally, the main current topic of research of CORE is described.
International Nuclear Information System (INIS)
Kurosaki, A.; Kozeki, M.
1981-01-01
Spectrum-compatible artificial time histories of ground motions are frequently used for the seismic design of nuclear power plant structures and components. However, statistical uncertainty of the responses of building structures and mechanical components mounted on the building (building-appendage systems) are anticipated, since an artificial time history is no more than one sample from a population of such time histories that match a specified design response spectrum. This uncertainty may spoil the reliability of the seismic design and therefore the extent of the uncertainty of the response characteristic is a matter of great concern. In this paper, above-mentioned uncertainty of the dynamic response characteristics of the building-appendage system to the spectrum-compatible artificial earthquake is investigated. (orig./RW)
Economics of human performance and systems total ownership cost.
Onkham, Wilawan; Karwowski, Waldemar; Ahram, Tareq Z
2012-01-01
Financial costs of investing in people is associated with training, acquisition, recruiting, and resolving human errors have a significant impact on increased total ownership costs. These costs can also affect the exaggerate budgets and delayed schedules. The study of human performance economical assessment in the system acquisition process enhances the visibility of hidden cost drivers which support program management informed decisions. This paper presents the literature review of human total ownership cost (HTOC) and cost impacts on overall system performance. Economic value assessment models such as cost benefit analysis, risk-cost tradeoff analysis, expected value of utility function analysis (EV), growth readiness matrix, multi-attribute utility technique, and multi-regressions model were introduced to reflect the HTOC and human performance-technology tradeoffs in terms of the dollar value. The human total ownership regression model introduces to address the influencing human performance cost component measurement. Results from this study will increase understanding of relevant cost drivers in the system acquisition process over the long term.
Huijnen, V.; Bouarar, I.; Chabrillat, S. H.; Christophe, Y.; Thierno, D.; Karydis, V.; Marecal, V.; Pozzer, A.; Flemming, J.
2017-12-01
Operational atmospheric composition analyses and forecasts such as developed in the Copernicus Atmosphere Monitoring Service (CAMS) rely on modules describing emissions, chemical conversion, transport and removal processing, as well as data assimilation methods. The CAMS forecasts can be used to drive regional air quality models across the world. Critical analyses of uncertainties in any of these processes are continuously needed to advance the quality of such systems on a global scale, ranging from the surface up to the stratosphere. With regard to the atmospheric chemistry to describe the fate of trace gases, the operational system currently relies on a modified version of the CB05 chemistry scheme for the troposphere combined with the Cariolle scheme to describe stratospheric ozone, as integrated in ECMWF's Integrated Forecasting System (IFS). It is further constrained by assimilation of satellite observations of CO, O3 and NO2. As part of CAMS we have recently developed three fully independent schemes to describe the chemical conversion throughout the atmosphere. These parameterizations originate from parent model codes in MOZART, MOCAGE and a combination of TM5/BASCOE. In this contribution we evaluate the correspondence and elemental differences in the performance of the three schemes in an otherwise identical model configuration (excluding data-assimilation) against a large range of in-situ and satellite-based observations of ozone, CO, VOC's and chlorine-containing trace gases for both troposphere and stratosphere. This analysis aims to provide a measure of model uncertainty in the operational system for tracers that are not, or poorly, constrained by data assimilation. It aims also to provide guidance on the directions for further model improvement with regard to the chemical conversion module.
Cost and Systems Analysis of Innovative Fuel Resources Concepts
Energy Technology Data Exchange (ETDEWEB)
Schneider, Erich [Univ. of Texas, Austin, TX (United States). Nuclear and Radiation Engineering Program; Byers, M. [Univ. of Texas, Austin, TX (United States). Nuclear and Radiation Engineering Program
2017-05-04
Economically recovered uranium from seawater can have a transformative effect on the way policy makers view the long-term viability of uranium based fuel cycles. Seawater uranium, even when estimated to cost more than terrestrially mined uranium, is integral in establishing an economic backstop, thus reducing uncertainty in future nuclear power costs. While a passive recovery scheme relying on a field of polymer adsorbents prepared via radiation induced grafting has long been considered the leading technology for full scale deployment, non-trivial cost and logistical barriers persist. Consequently, university partners of the nation-wide consortium for seawater uranium recovery have developed variants of this technology, each aiming to address a substantial weakness. The focus of this NEUP project is the economic impacts of the proposed variant technologies. The team at University of Alabama has pursued an adsorbent synthesis method that replaces the synthetic fiber backbone with a natural waste product. Chitin fibers suitable for ligand grafting have been prepared from shrimp shell waste. These environmental benefits could be realized at a comparable cost to the reference fiber so long as the uptake can be increased or the chemical consumption cost decreased.
Jin, S W; Li, Y P; Xu, L P
2018-07-01
A bi-level fuzzy programming (BFLP) method was developed for energy systems planning (ESP) and carbon dioxide (CO 2 ) mitigation under uncertainty. BFLP could handle fuzzy information and leader-follower problem in decision-making processes. It could also address the tradeoffs among different decision makers in two decision-making levels through prioritizing the most important goal. Then, a BFLP-ESP model was formulated for planning energy system of Beijing, in which the upper-level objective is to minimize CO 2 emission and the lower-level objective is to minimize the system cost. Results provided a range of decision alternatives that corresponded to a tradeoff between system optimality and reliability under uncertainty. Compared to the single-level model with a target to minimize system cost, the amounts of pollutant/CO 2 emissions from BFLP-ESP were reduced since the study system would prefer more clean energies (i.e. natural gas, LPG and electricity) to replace coal fuel. Decision alternatives from BFLP were more beneficial for supporting Beijing to adjust its energy mix and enact its emission-abatement policy. Results also revealed that the low-carbon policy for power plants (e.g., shutting down all coal-fired power plants) could lead to a potentially increment of imported energy for Beijing, which would increase the risk of energy shortage. The findings could help decision makers analyze the interactions between different stakeholders in ESP and provide useful information for policy design under uncertainty. Copyright © 2018 Elsevier Inc. All rights reserved.
Prinn, R. G.
2013-12-01
The world is facing major challenges that create tensions between human development and environmental sustenance. In facing these challenges, computer models are invaluable tools for addressing the need for probabilistic approaches to forecasting. To illustrate this, I use the MIT Integrated Global System Model framework (IGSM; http://globalchange.mit.edu ). The IGSM consists of a set of coupled sub-models of global economic and technological development and resultant emissions, and physical, dynamical and chemical processes in the atmosphere, land, ocean and ecosystems (natural and managed). Some of the sub-models have both complex and simplified versions available, with the choice of which version to use being guided by the questions being addressed. Some sub-models (e.g.urban air pollution) are reduced forms of complex ones created by probabilistic collocation with polynomial chaos bases. Given the significant uncertainties in the model components, it is highly desirable that forecasts be probabilistic. We achieve this by running 400-member ensembles (Latin hypercube sampling) with different choices for key uncertain variables and processes within the human and natural system model components (pdfs of inputs estimated by model-observation comparisons, literature surveys, or expert elicitation). The IGSM has recently been used for probabilistic forecasts of climate, each using 400-member ensembles: one ensemble assumes no explicit climate mitigation policy and others assume increasingly stringent policies involving stabilization of greenhouse gases at various levels. These forecasts indicate clearly that the greatest effect of these policies is to lower the probability of extreme changes. The value of such probability analyses for policy decision-making lies in their ability to compare relative (not just absolute) risks of various policies, which are less affected by the earth system model uncertainties. Given the uncertainties in forecasts, it is also clear that
Ritchie, W. J.; Dowlatabadi, H.
2017-12-01
Climate change modeling relies on projections of future greenhouse gas emissions and other phenomena leading to changes in planetary radiative forcing (RF). Pathways for long-run fossil energy use that map to total forcing outcomes are commonly depicted with integrated assessment models (IAMs). IAMs structure outlooks for 21st-century emissions with various theories for developments in demographics, economics, land-use, energy markets and energy service demands. These concepts are applied to understand global changes in two key factors relevant for scenarios of carbon emissions: total energy use (E) this century and the carbon intensity of that energy (F/E). A simple analytical and graphical approach can also illustrate the full range of outcomes for these variables to determine if IAMs provide sufficient coverage of the uncertainty space for future energy use. In this talk, we present a method for understanding uncertainties relevant to RF scenario components in a phase space. The phase space of a dynamic system represents significant factors as axes to capture the full range of physically possible states. A two-dimensional phase space of E and F/E presents the possible system states that can lead to various levels of total 21st-century carbon emissions. Once defined in this way, a phase space of these energy system coordinates allows for rapid characterization of large IAM scenario sets with machine learning techniques. This phase space method is applied to the levels of RF described by the Representative Concentration Pathways (RCPs). The resulting RCP phase space identifies characteristics of the baseline energy system outlooks provided by IAMs for IPCC Working Group III. We conduct a k-means cluster analysis to distinguish the major features of IAM scenarios for each RCP range. Cluster analysis finds the IAM scenarios in AR5 illustrate RCPs with consistent combinations of energy resources. This suggests IAM scenarios understate uncertainty ranges for future
Su, Bin-Guang; Chen, Shao-Fen; Yeh, Shu-Hsing; Shih, Po-Wen; Lin, Ching-Chiang
2016-11-01
To cope with the government's policies to reduce medical costs, Taiwan's healthcare service providers are striving to survive by pursuing profit maximization through cost control. This article aimed to present the results of cost evaluation using activity-based costing performed in the laboratory in order to throw light on the differences between costs and the payment system of National Health Insurance (NHI). This study analyzed the data of costs and income of the clinical laboratory. Direct costs belong to their respective sections of the department. The department's shared costs, including public expenses and administrative assigned costs, were allocated to the department's respective sections. A simple regression equation was created to predict profit and loss, and evaluate the department's break-even point, fixed cost, and contribution margin ratio. In clinical chemistry and seroimmunology sections, the cost per test was lower than the NHI payment and their major laboratory tests had revenues with the profitability ratio of 8.7%, while the other sections had a higher cost per test than the NHI payment and their major tests were in deficit. The study found a simple linear regression model as follows: "Balance=-84,995+0.543×income (R2=0.544)". In order to avoid deficit, laboratories are suggested to increase test volumes, enhance laboratory test specialization, and become marginal scale. A hospital could integrate with regional medical institutions through alliances or OEM methods to increase volumes to reach marginal scale and reduce laboratory costs, enhancing the level and quality of laboratory medicine.
Value and cost analyses for solar thermal-storage systems
Energy Technology Data Exchange (ETDEWEB)
Luft, W.; Copeland, R.J.
1983-04-01
Value and cost data for thermal energy storage are presented for solar thermal central receiver systems for which thermal energy storage appears to be attractive. Both solar thermal electric power and industrial process heat applications are evaluated. The value of storage is based on the cost for fossil fuel and solar thermal collector systems in 1990. The costing uses a standard lifetime methodology with the storage capacity as a parameter. Both value and costs are functions of storage capacity. However, the value function depends on the application. Value/cost analyses for first-generation storage concepts for five central receiver systems (molten salt, water/steam, organic fluid, air, and liquid metal) established the reference against which new systems were compared. Some promising second-generation energy storage concepts have been identified, and some more advanced concepts have also been evaluated.
Computerized management report system for monitoring manpower and cost
International Nuclear Information System (INIS)
Bullington, V.R.; Stephenson, R.L.; Cardwell, R.G.
1980-04-01
Although most cost systems offer complete detail and traceability, not all provide timely detail in a concise form useful to senior management. This system was developed for a multifunction research organization funded from many sources. It extracts cost and manpower data from the general cost systems, summarizes it, compares it by program with previous cost periods, and presents it with minimum detail yet with maximum overview. The system monitors the basic manpower distribution of effort at the source, that is, the division time-card input. Cost data are taken from the central computer ahead of the print-out and report-distribution steps; thus, the summary information is available several days ahead of the detailed reports. This procedure has been regularly used for several months, and has proven to be a valuable tool in management action and planning. 9 figures
SCATS: SRB Cost Accounting and Tracking System handbook
Zorv, R. B.; Stewart, R. D.; Coley, G.; Higginbotham, M.
1978-01-01
The Solid Rocket Booster Cost Accounting and Tracking System (SCATS) which is an automatic data processing system designed to keep a running account of the number, description, and estimated cost of Level 2, 3, and 4 changes is described. Although designed specifically for the Space Shuttle Solid Rocket Booster Program, the ADP system can be used for any other program that has a similar structure for recording, reporting, and summing numbers and costs of changes. The program stores the alpha-numeric designators for changes, government estimated costs, proposed costs, and negotiated value in a MIRADS (Marshall Information Retrieval and Display System) format which permits rapid access, manipulation, and reporting of current change status. Output reports listing all changes, totals of each level, and totals of all levels, can be derived for any calendar interval period.
International Nuclear Information System (INIS)
Sullivan, W.G.
1977-07-01
Steam-electric generation plants are evaluated on a benefit-cost basis. Non-economic factors in the development and application of a procedure for quantifying environmental uncertainties of a nuclear power plant are discussed. By comparing monetary costs of a particular power plant assessed in Part 1 with non-monetary values arrived at in Part 2 and using an evaluation procedure developed in this study, a proposed power plant can be selected as a preferred alternative. This procedure enables policymakers to identify the incremental advantages and disadvantages of different power plants in view of their geographic locations. The report presents the evaluation procedure on a task by task basis and shows how it can be applied to a particular power plant. Because of the lack of objective data, it draws heavily on subjectively-derived inputs of individuals who are knowledgeable about the plant being investigated. An abbreviated study at another power plant demonstrated the transferability of the general evaluation procedure. Included in the appendices are techniques for developing scoring functions and a user's manual for the Fortran IV Program
Energy Technology Data Exchange (ETDEWEB)
Prather, Michael J. [Univ. of California, Irvine, CA (United States); Hsu, Juno [Univ. of California, Irvine, CA (United States); Nicolau, Alex [Univ. of California, Irvine, CA (United States); Veidenbaum, Alex [Univ. of California, Irvine, CA (United States); Smith, Philip Cameron [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Bergmann, Dan [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2014-11-07
Atmospheric chemistry controls the abundances and hence climate forcing of important greenhouse gases including N_{2}O, CH_{4}, HFCs, CFCs, and O_{3}. Attributing climate change to human activities requires, at a minimum, accurate models of the chemistry and circulation of the atmosphere that relate emissions to abundances. This DOE-funded research provided realistic, yet computationally optimized and affordable, photochemical modules to the Community Earth System Model (CESM) that augment the CESM capability to explore the uncertainty in future stratospheric-tropospheric ozone, stratospheric circulation, and thus the lifetimes of chemically controlled greenhouse gases from climate simulations. To this end, we have successfully implemented Fast-J (radiation algorithm determining key chemical photolysis rates) and Linoz v3.0 (linearized photochemistry for interactive O_{3}, N_{2}O, NO_{y} and CH_{4}) packages in LLNL-CESM and for the first time demonstrated how change in O2 photolysis rate within its uncertainty range can significantly impact on the stratospheric climate and ozone abundances. From the UCI side, this proposal also helped LLNL develop a CAM-Superfast Chemistry model that was implemented for the IPCC AR5 and contributed chemical-climate simulations to CMIP5.
Uncertainty and sensitivity analysis of electro-mechanical impedance based SHM system
International Nuclear Information System (INIS)
Rosiek, M; Martowicz, A; Uhl, T
2010-01-01
The paper deals with the application of uncertainty and sensitivity analysis performed for FE simulations for electro-mechanical impedance based SHM system. The measurement of electro-mechanical impedance allows to follow changes of mechanical properties of monitored construction. Therefore it can be effectively applied to conclude about presence of damage. Coupled FE simulations have been carried out for simultaneous consideration of both structural dynamics and piezoelectric properties of a simple beam with bonded transducer. Several indexes have been used to assess the damage growth. In the paper the results obtained with both deterministic and stochastic simulations are shown and discussed. First, the relationship between size of introduced damage and its indexes has been studied. Second, ranges of variation of selected model properties have been assumed to find relationships between them and damage indexes. The most influential parameters have been found. Finally, the overall propagation of considered uncertainty has been assessed and related histograms plotted to discuss effectiveness and robustness of tested damage indexes based on the measurement of electro-mechanical impedance.
FEDERAL PENSIONS: Judicial Survivors Annuities System Costs
National Research Council Canada - National Science Library
2002-01-01
...) specifying that we review certain aspects of the Judicial Survivors' Annuities System (JSAS), which is one of several survivor benefit plans applicable to particular groups of federal employees...
Directory of Open Access Journals (Sweden)
Simon van Mourik
2014-06-01
Full Text Available Multi-parameter models in systems biology are typically ‘sloppy’: some parameters or combinations of parameters may be hard to estimate from data, whereas others are not. One might expect that parameter uncertainty automatically leads to uncertain predictions, but this is not the case. We illustrate this by showing that the prediction uncertainty of each of six sloppy models varies enormously among different predictions. Statistical approximations of parameter uncertainty may lead to dramatic errors in prediction uncertainty estimation. We argue that prediction uncertainty assessment must therefore be performed on a per-prediction basis using a full computational uncertainty analysis. In practice this is feasible by providing a model with a sample or ensemble representing the distribution of its parameters. Within a Bayesian framework, such a sample may be generated by a Markov Chain Monte Carlo (MCMC algorithm that infers the parameter distribution based on experimental data. Matlab code for generating the sample (with the Differential Evolution Markov Chain sampler and the subsequent uncertainty analysis using such a sample, is supplied as Supplemental Information.
Energy Technology Data Exchange (ETDEWEB)
Panka, Istvan; Hegyi, Gyoergy; Maraczy, Csaba; Temesvari, Emese [Hungarian Academy of Sciences, Budapest (Hungary). Reactor Analysis Dept.
2017-11-15
The best-estimate KARATE code system has been widely used for core design calculations and simulations of slow transients of VVER reactors. Recently there has been an increasing need for assessing the uncertainties of such calculations by propagating the basic input uncertainties of the models through the full calculation chain. In order to determine the uncertainties of quantities of interest during the burnup, the statistical version of the KARATE code system has been elaborated. In the first part of the paper, the main features of the new code system are discussed. The applied statistical method is based on Monte-Carlo sampling of the considered input data taking into account mainly the covariance matrices of the cross sections and/or the technological uncertainties. In the second part of the paper, only the uncertainties of cross sections are considered and an equilibrium cycle related to a VVER-440 type reactor is investigated. The burnup dependence of the uncertainties of some safety related parameters (e.g. critical boron concentration, rod worth, feedback coefficients, assembly-wise radial power and burnup distribution) are discussed and compared to the recently used limits.
Waste management facilities cost information: System cost model product description. Revision 2
International Nuclear Information System (INIS)
Lundeen, A.S.; Hsu, K.M.; Shropshire, D.E.
1996-02-01
In May of 1994, Lockheed Idaho Technologies Company (LITCO) in Idaho Falls, Idaho and subcontractors developed the System Cost Model (SCM) application. The SCM estimates life-cycle costs of the entire US Department of Energy (DOE) complex for designing; constructing; operating; and decommissioning treatment, storage, and disposal (TSD) facilities for mixed low-level, low-level, transuranic, and mixed transuranic waste. The SCM uses parametric cost functions to estimate life-cycle costs for various treatment, storage, and disposal modules which reflect planned and existing facilities at DOE installations. In addition, SCM can model new facilities based on capacity needs over the program life cycle. The SCM also provides transportation costs for DOE wastes. Transportation costs are provided for truck and rail and include transport of contact-handled, remote-handled, and alpha (transuranic) wastes. The user can provide input data (default data is included in the SCM) including the volume and nature of waste to be managed, the time period over which the waste is to be managed, and the configuration of the waste management complex (i.e., where each installation's generated waste will be treated, stored, and disposed). Then the SCM uses parametric cost equations to estimate the costs of pre-operations (designing), construction costs, operation management, and decommissioning these waste management facilities
The System Cost Model: A tool for life cycle cost and risk analysis
International Nuclear Information System (INIS)
Hsu, K.; Lundeen, A.; Shropshire, D.; Sherick, M.
1996-01-01
In May of 1994, Lockheed Idaho Technologies Company (LITCO) in Idaho Falls, Idaho and subcontractors began development of the System Cost Model (SCM) application. The SCM estimates life cycle costs of the entire US Department of Energy (DOE) complex for designing; constructing; operating; and decommissioning treatment, storage, and disposal (TSD) facilities for mixed low-level, low-level, and transuranic waste. The SCM uses parametric cost functions to estimate life cycle costs for various treatment, storage, and disposal modules which reflect planned and existing waste management facilities at DOE installations. In addition, SCM can model new TSD facilities based on capacity needs over the program life cycle. The user can provide input data (default data is included in the SCM) including the volume and nature of waste to be managed, the time period over which the waste is to be managed, and the configuration of the waste management complex (i.e., where each installation's generated waste will be treated, stored, and disposed). Then the SCM uses parametric cost equations to estimate the costs of pre-operations (designing), construction, operations and maintenance, and decommissioning these waste management facilities. The SCM also provides transportation costs for DOE wastes. Transportation costs are provided for truck and rail and include transport of contact-handled, remote-handled, and alpha (transuranic) wastes. A complement to the SCM is the System Cost Model-Risk (SCM-R) model, which provides relative Environmental, Safety, and Health (ES and H) risk information. A relative ES and H risk basis has been developed and applied by LITCO at the INEL. The risk basis is now being automated in the SCM-R to facilitate rapid risk analysis of system alternatives. The added risk functionality will allow combined cost and risk evaluation of EM alternatives
O'Brien, B J; Sculpher, M J
2000-05-01
Current principles of cost-effectiveness analysis emphasize the rank ordering of programs by expected economic return (eg, quality-adjusted life-years gained per dollar expended). This criterion ignores the variance associated with the cost-effectiveness of a program, yet variance is a common measure of risk when financial investment options are appraised. Variation in health care program return is likely to be a criterion of program selection for health care managers with fixed budgets and outcome performance targets. Characterizing health care resource allocation as a risky investment problem, we show how concepts of portfolio analysis from financial economics can be adopted as a conceptual framework for presenting cost-effectiveness data from multiple programs as mean-variance data. Two specific propositions emerge: (1) the current convention of ranking programs by expected return is a special case of the portfolio selection problem in which the decision maker is assumed to be indifferent to risk, and (2) for risk-averse decision makers, the degree of joint risk or covariation in cost-effectiveness between programs will create incentives to diversify an investment portfolio. The conventional normative assumption of risk neutrality for social-level public investment decisions does not apply to a large number of health care resource allocation decisions in which health care managers seek to maximize returns subject to budget constraints and performance targets. Portfolio theory offers a useful framework for studying mean-variance tradeoffs in cost-effectiveness and offers some positive predictions (and explanations) of actual decision making in the health care sector.
Uncertainty Evaluation of the Thermal Expansion of Gd2O3-ZrO2 with a System Calibration Factor
International Nuclear Information System (INIS)
Park, Chang Je; Kang, Kweon Ho; Na, Sang Ho; Song, Kee Chan
2007-01-01
Both gadolinia (Gd 2 O 3 ) and zirconia (ZrO 2 ) are widely used in the nuclear industry, including a burnable absorber and additives in the fabrication of a simulated fuel. Thermal expansions of a mixture of gadolinia (Gd 2 O 3 ) 20 mol% and zirconia (ZrO 2 ) 80 mol% were measured by using a dilatometer (DIL402C) from room temperature to 1500 .deg. C. Uncertainties in the measurement should be quantified based on statistics. Referring to the ISO (International Organization for Standardization) guide, the uncertainties of the thermal expansion were quantified for three parts - the initial length, the length variation, and the system calibration factor. The whole system, the dilatometer, is composed of many complex sub-systems and in fact it is difficult to consider all the uncertainties of the sub-systems. Thus, the system calibration factor was introduced with a standard material for the uncertainty evaluation. In this study, a new system calibration factor was formulated in a multiplicative way. Further, the effect of calibration factor with random deviation was investigated for the uncertainty evaluation of a thermal expansion
Energy Technology Data Exchange (ETDEWEB)
Lester-Coll, Nataniel H., E-mail: nataniel.lester-coll@yale.edu [Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut (United States); Rutter, Charles E.; Bledsoe, Trevor J. [Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut (United States); Goldberg, Sarah B. [Department of Medicine (Medical Oncology), Yale University School of Medicine, New Haven, Connecticut (United States); Decker, Roy H.; Yu, James B. [Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut (United States)
2016-06-01
Introduction: Pulmonary oligometastases have conventionally been managed with surgery and/or systemic therapy. However, given concerns about the high cost of systemic therapy and improvements in local treatment of metastatic cancer, the optimal cost-effective management of these patients is unclear. Therefore, we sought to assess the cost-effectiveness of initial management strategies for pulmonary oligometastases. Methods and Materials: A cost-effectiveness analysis using a Markov modeling approach was used to compare average cumulative costs, quality adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs) among 3 initial disease management strategies: video-assisted thoracic surgery (VATS) wedge resection, stereotactic body radiation therapy (SBRT), and systemic therapy among 5 different cohorts of patient disease: (1) melanoma; (2) non-small cell lung cancer adenocarcinoma without an EGFR mutation (NSCLC AC); (3) NSCLC with an EGFR mutation (NSCLC EGFRm AC); (4) NSCLC squamous cell carcinoma (NSCLC SCC); and (5) colon cancer. One-way sensitivity analyses and probabilistic sensitivity analyses were performed to analyze uncertainty with regard to model parameters. Results: In the base case, SBRT was cost effective for melanoma, with costs/net QALYs of $467,787/0.85. In patients with NSCLC, the most cost-effective strategies were SBRT for AC ($156,725/0.80), paclitaxel/carboplatin for SCC ($123,799/0.48), and erlotinib for EGFRm AC ($147,091/1.90). Stereotactic body radiation therapy was marginally cost-effective for EGFRm AC compared to erlotinib with an incremental cost-effectiveness ratio of $126,303/QALY. For colon cancer, VATS wedge resection ($147,730/2.14) was the most cost-effective strategy. Variables with the greatest influence in the model were erlotinib-associated progression-free survival (EGFRm AC), toxicity (EGFRm AC), cost of SBRT (NSCLC SCC), and patient utilities (all histologies). Conclusions: Video-assisted thoracic
A Cost Effective System Design Approach for Critical Space Systems
Abbott, Larry Wayne; Cox, Gary; Nguyen, Hai
2000-01-01
NASA-JSC required an avionics platform capable of serving a wide range of applications in a cost-effective manner. In part, making the avionics platform cost effective means adhering to open standards and supporting the integration of COTS products with custom products. Inherently, operation in space requires low power, mass, and volume while retaining high performance, reconfigurability, scalability, and upgradability. The Universal Mini-Controller project is based on a modified PC/104-Plus architecture while maintaining full compatibility with standard COTS PC/104 products. The architecture consists of a library of building block modules, which can be mixed and matched to meet a specific application. A set of NASA developed core building blocks, processor card, analog input/output card, and a Mil-Std-1553 card, have been constructed to meet critical functions and unique interfaces. The design for the processor card is based on the PowerPC architecture. This architecture provides an excellent balance between power consumption and performance, and has an upgrade path to the forthcoming radiation hardened PowerPC processor. The processor card, which makes extensive use of surface mount technology, has a 166 MHz PowerPC 603e processor, 32 Mbytes of error detected and corrected RAM, 8 Mbytes of Flash, and I Mbytes of EPROM, on a single PC/104-Plus card. Similar densities have been achieved with the quad channel Mil-Std-1553 card and the analog input/output cards. The power management built into the processor and its peripheral chip allows the power and performance of the system to be adjusted to meet the requirements of the application, allowing another dimension to the flexibility of the Universal Mini-Controller. Unique mechanical packaging allows the Universal Mini-Controller to accommodate standard COTS and custom oversized PC/104-Plus cards. This mechanical packaging also provides thermal management via conductive cooling of COTS boards, which are typically
The importance of fixed costs in animal health systems.
Tisdell, C A; Adamson, D
2017-04-01
In this paper, the authors detail the structure and optimal management of health systems as influenced by the presence and level of fixed costs. Unlike variable costs, fixed costs cannot be altered, and are thus independent of the level of veterinary activity in the short run. Their importance is illustrated by using both single-period and multi-period models. It is shown that multi-stage veterinary decision-making can often be envisaged as a sequence of fixed-cost problems. In general, it becomes clear that, the higher the fixed costs, the greater the net benefit of veterinary activity must be, if such activity is to be economic. The authors also assess the extent to which it pays to reduce fixed costs and to try to compensate for this by increasing variable costs. Fixed costs have major implications for the industrial structure of the animal health products industry and for the structure of the private veterinary services industry. In the former, they favour market concentration and specialisation in the supply of products. In the latter, they foster increased specialisation. While cooperation by individual farmers may help to reduce their individual fixed costs, the organisational difficulties and costs involved in achieving this cooperation can be formidable. In such cases, the only solution is government provision of veterinary services. Moreover, international cooperation may be called for. Fixed costs also influence the nature of the provision of veterinary education.
Fuzzy parametric uncertainty analysis of linear dynamical systems: A surrogate modeling approach
Chowdhury, R.; Adhikari, S.
2012-10-01
Uncertainty propagation engineering systems possess significant computational challenges. This paper explores the possibility of using correlated function expansion based metamodelling approach when uncertain system parameters are modeled using Fuzzy variables. In particular, the application of High-Dimensional Model Representation (HDMR) is proposed for fuzzy finite element analysis of dynamical systems. The HDMR expansion is a set of quantitative model assessment and analysis tools for capturing high-dimensional input-output system behavior based on a hierarchy of functions of increasing dimensions. The input variables may be either finite-dimensional (i.e., a vector of parameters chosen from the Euclidean space RM) or may be infinite-dimensional as in the function space CM[0,1]. The computational effort to determine the expansion functions using the alpha cut method scales polynomially with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is integrated with a commercial Finite Element software. Modal analysis of a simplified aircraft wing with Fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations.
Ding, Da-Wei; Liu, Fang-Fang; Chen, Hui; Wang, Nian; Liang, Dong
2017-12-01
In this paper, a simplest fractional-order delayed memristive chaotic system is proposed in order to control the chaos behaviors via sliding mode control strategy. Firstly, we design a sliding mode control strategy for the fractional-order system with time delay to make the states of the system asymptotically stable. Then, we obtain theoretical analysis results of the control method using Lyapunov stability theorem which guarantees the asymptotic stability of the non-commensurate order and commensurate order system with and without uncertainty and an external disturbance. Finally, numerical simulations are given to verify that the proposed sliding mode control method can eliminate chaos and stabilize the fractional-order delayed memristive system in a finite time. Supported by the National Nature Science Foundation of China under Grant No. 61201227, Funding of China Scholarship Council, the Natural Science Foundation of Anhui Province under Grant No. 1208085M F93, 211 Innovation Team of Anhui University under Grant Nos. KJTD007A and KJTD001B
Practical impulsive synchronization of chaotic systems with parametric uncertainty and mismatch
International Nuclear Information System (INIS)
Wen, C.Y.; Ji, Y.; Li, Z.G.
2007-01-01
Recently, there has been increasing interest in the synchronization of two chaotic systems and some significant results have been reported. In these results, a strong assumption that the two chaotic systems should be identical, i.e., without any mismatch, is imposed. Furthermore, system parameters are also assumed known exactly. Clearly, these are impractical. In this Letter, pure impulsive synchronization is considered. We quantitatively establish a relationship between a pre-specified bound of the synchronization error and the length of impulsive intervals in the presence of both parametric uncertainties and mismatch between the two systems. This is the first available result in the area, to the knowledge of the authors. With such a relationship as a guideline to choose impulsive intervals, a practical impulsive synchronization scheme is obtained. With the proposed scheme, the magnitude of the synchronization error is theoretically ensured to approach to and stay within the pre-specified bound which can be arbitrarily small. Simulation studies on the Lorenz system also verify the effectiveness of the proposed scheme
Analysis of costs-benefits tradeoffs of complex security systems
International Nuclear Information System (INIS)
Hicks, M.J.
1996-01-01
Essential to a systems approach to design of security systems is an analysis of the cost effectiveness of alternative designs. While the concept of analysis of costs and benefits is straightforward, implementation can be at the least tedious and, for complex designs and alternatives, can become nearly intractable without the help of structured analysis tools. PACAIT--Performance and Cost Analysis Integrated Tools--is a prototype tool. The performance side of the analysis collates and reduces data from ASSESS, and existing DOE PC-based security systems performance analysis tool. The costs side of the analysis uses ACE, an existing DOD PC-based costs analysis tool. Costs are reported over the full life-cycle of the system, that is, the costs to procure, operate, maintain and retire the system and all of its components. Results are collected in Microsoft reg-sign Excel workbooks and are readily available to analysts and decision makers in both tabular and graphical formats and at both the system and path-element levels
Crump, William J.; Janik, Daniel S.; Thomas, L. Dale
1990-01-01
U.S. space missions have to this point used water either made on board or carried from earth and discarded after use. For Space Station Freedom, long duration life support will include air and water recycling using a series of physical-chemical subsystems. The Environmental Control and Life Support System (ECLSS) designed for this application must be tested extensively at all stages of hardware maturity. Human test subjects are required to conduct some of these tests, and the risks associated with the use of development hardware must be addressed. Federal guidelines for protection of human subjects require careful consideration of risks and potential benefits by an Institutional Review Board (IRB) before and during testing. This paper reviews the ethical principles guiding this consideration, details the problems and uncertainties inherent in current hardware testing, and presents an incremental approach to risk assessment for ECLSS testing.
Density meter algorithm and system for estimating sampling/mixing uncertainty
International Nuclear Information System (INIS)
Shine, E.P.
1986-01-01
The Laboratories Department at the Savannah River Plant (SRP) has installed a six-place density meter with an automatic sampling device. This paper describes the statistical software developed to analyze the density of uranyl nitrate solutions using this automated system. The purpose of this software is twofold: to estimate the sampling/mixing and measurement uncertainties in the process and to provide a measurement control program for the density meter. Non-uniformities in density are analyzed both analytically and graphically. The mean density and its limit of error are estimated. Quality control standards are analyzed concurrently with process samples and used to control the density meter measurement error. The analyses are corrected for concentration due to evaporation of samples waiting to be analyzed. The results of this program have been successful in identifying sampling/mixing problems and controlling the quality of analyses
Density meter algorithm and system for estimating sampling/mixing uncertainty
International Nuclear Information System (INIS)
Shine, E.P.
1986-01-01
The Laboratories Department at the Savannah River Plant (SRP) has installed a six-place density meter with an automatic sampling device. This paper describes the statisical software developed to analyze the density of uranyl nitrate solutions using this automated system. The purpose of this software is twofold: to estimate the sampling/mixing and measurement uncertainties in the process and to provide a measurement control program for the density meter. Non-uniformities in density are analyzed both analytically and graphically. The mean density and its limit of error are estimated. Quality control standards are analyzed concurrently with process samples and used to control the density meter measurement error. The analyses are corrected for concentration due to evaporation of samples waiting to be analyzed. The results of this program have been successful in identifying sampling/mixing problems and controlling the quality of analyses
Cost-efficiency of animal welfare in broiler production systems
Gocsik, Éva; Brooshooft, Suzanne D.; Jong, de Ingrid C.; Saatkamp, Helmut W.
2016-01-01
Broiler producers operate in a highly competitive and cost-price driven environment. In addition, in recent years the societal pressure to improve animal welfare (AW) in broiler production systems is increasing. Hence, from an economic and decision making point of view, the cost-efficiency of
Systemic cost-effectiveness analysis of food hazard reduction
DEFF Research Database (Denmark)
Jensen, Jørgen Dejgård; Lawson, Lartey Godwin; Lund, Mogens
2015-01-01
stage are considered. Cost analyses are conducted for different risk reduction targets and for three alternative scenarios concerning the acceptable range of interventions. Results demonstrate that using a system-wide policy approach to risk reduction can be more cost-effective than a policy focusing...
International Nuclear Information System (INIS)
Maheri, Alireza
2014-01-01
Reliability of a hybrid renewable energy system (HRES) strongly depends on various uncertainties affecting the amount of power produced by the system. In the design of systems subject to uncertainties, both deterministic and nondeterministic design approaches can be adopted. In a deterministic design approach, the designer considers the presence of uncertainties and incorporates them indirectly into the design by applying safety factors. It is assumed that, by employing suitable safety factors and considering worst-case-scenarios, reliable systems can be designed. In fact, the multi-objective optimisation problem with two objectives of reliability and cost is reduced to a single-objective optimisation problem with the objective of cost only. In this paper the competence of deterministic design methods in size optimisation of reliable standalone wind–PV–battery, wind–PV–diesel and wind–PV–battery–diesel configurations is examined. For each configuration, first, using different values of safety factors, the optimal size of the system components which minimises the system cost is found deterministically. Then, for each case, using a Monte Carlo simulation, the effect of safety factors on the reliability and the cost are investigated. In performing reliability analysis, several reliability measures, namely, unmet load, blackout durations (total, maximum and average) and mean time between failures are considered. It is shown that the traditional methods of considering the effect of uncertainties in deterministic designs such as design for an autonomy period and employing safety factors have either little or unpredictable impact on the actual reliability of the designed wind–PV–battery configuration. In the case of wind–PV–diesel and wind–PV–battery–diesel configurations it is shown that, while using a high-enough margin of safety in sizing diesel generator leads to reliable systems, the optimum value for this margin of safety leading to a
Internalising external costs of electricity and heat production in a municipal energy system
International Nuclear Information System (INIS)
Holmgren, Kristina; Amiri, Shahnaz
2007-01-01
Both energy supply and waste treatment give rise to negative effects on the environment, so-called external effects. In this study, monetary values on external costs collected from the EU's ExternE project are used to evaluate inclusion of these costs in comparison with an energy utility perspective including present policy instruments. The studied object is a municipal district heating system with a waste incineration plant as the base supplier of heat. The evaluation concerns fuels used for heat production and total electricity production, for scenarios with external costs included and for a scenario using the present policy instrument. Impacts of assumptions on marginal power producers (coal or natural gas power plants) are investigated, since locally produced electricity is assumed to replace marginal power and thus is credited for the avoided burden. Varying levels of external costs for carbon dioxide emissions are analysed. The method used is an economic optimisation model, MODEST. The conclusion is that present policy instruments are strong incentives for cogeneration, even when external costs are included. Waste is fully utilised in all scenarios. In cases where coal is the marginal power producer, more electricity is produced; when natural gas is the marginal power producer, less is produced. There are several uncertainties in the data for external costs, both methodological and ethical. In the ExternE data, not all environmental impacts are included. For waste incineration, ashes are not included, and another difficulty is how to treat the avoided burden of other waste treatment methods
da Silva, A.; Redder, C. R.
2010-12-01
MERRA is a NASA reanalysis for the satellite era using a major new version of the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5). The Project focuses on historical analyses of the hydrological cycle on a broad range of weather and climate time scales and places the NASA EOS suite of observations in a climate context. The characterization of uncertainty in reanalysis fields is a commonly requested feature by users of such data. While intercomparison with reference data sets is common practice for ascertaining the realism of the datasets, such studies typically are restricted to long term climatological statistics and seldom provide state dependent measures of the uncertainties involved. In principle, variational data assimilation algorithms have the ability of producing error estimates for the analysis variables (typically surface pressure, winds, temperature, moisture and ozone) consistent with the assumed background and observation error statistics. However, these "perceived error estimates" are expensive to obtain and are limited by the somewhat simplistic errors assumed in the algorithm. The observation minus forecast residuals (innovations) by-product of any assimilation system constitutes a powerful tool for estimating the systematic and random errors in the analysis fields. Unfortunately, such data is usually not readily available with reanalysis products, often requiring the tedious decoding of large datasets and not so-user friendly file formats. With MERRA we have introduced a gridded version of the observations/innovations used in the assimilation process, using the same grid and data formats as the regular datasets. Such dataset empowers the user with the ability of conveniently performing observing system related analysis and error estimates. The scope of this dataset will be briefly described. We will present a systematic analysis of MERRA innovation time series for the conventional observing system, including maximum
Consumer Dispersion and Logistics Costs in Various Distribution Systems
DEFF Research Database (Denmark)
Turkensteen, Marcel; Klose, Andreas
We address the relationship between the geographical dispersion of a set of demand points and the expected logistics costs. This is relevant in the strategic marketing decision which groups of consumers to target. We devise quickly computable measures for the logistics costs. In our experiments......, dispersed sets of demand points are created. For various types of distribution systems, expected logistics costs are computed using continuous approximation, location and routing methodologies. We find that the average distance between locations is an effective estimate of the logistics costs....
Construction of VLCC marine oil storage cost index system
Li, Yuan; Li, Yule; Lu, Jinshu; Wu, Wenfeng; Zhu, Faxin; Chen, Tian; Qin, Beichen
2018-04-01
VLCC as the research object, the basic knowledge of VLCC is summarized. According to the phenomenon that VLCC is applied to offshore oil storage gradually, this paper applies the theoretical analysis method to analyze the excess capacity from VLCC, the drop of oil price, the aging VLCC is more suitable for offshore storage The paper analyzes the reason of VLCC offshore oil storage from three aspects, analyzes the cost of VLCC offshore storage from the aspects of manpower cost and shipping cost, and constructs the cost index system of VLCC offshore oil storage.
International Nuclear Information System (INIS)
Su Rui; Wang Ju; Chen Weiming; Zong Zihua; Zhao Honggang
2008-01-01
CRP-GEORC concept model is an artificial system of geological disposal for High-Level radioactive waste. Sensitivity analysis and uncertainties simulation of the migration of radionuclide Se-79 and I-129 in the far field of this system by using GoldSim Code have been conducted. It can be seen from the simulation results that variables used to describe the geological features and characterization of groundwater flow are sensitive variables of whole geological disposal system. The uncertainties of parameters have remarkable influence on the simulation results. (authors)
Software Intensive Systems Cost and Schedule Estimation
2013-06-13
of labor counted in or across each activity. The activity data in the SRDR is reported following the [ ISO 12207 ] processes for software development...Release Table 19 ISO /IEC 12207 Development Activities System requirements analysis System architectural design A ct iv iti es in S RD R da ta... 12207 ] ISO /IEC 12207 , International Standard on Information Technology Software Lifecycle Processes, International Organization for Standardization
Energy costs and Portland water supply system
Energy Technology Data Exchange (ETDEWEB)
Elliott, W.M.; Hawley, R.P.
1981-10-01
The changing role of electrical energy on the Portland, Oregon, municipal-water-supply system is presented. Portland's actions in energy conservation include improved operating procedures, pump modifications, and modifications to the water system to eliminate pumping. Portland is implementing a small hydroelectric project at existing water-supply dams to produce an additional source of power for the area. Special precautions in construction and operation are necessary to protect the high quality of the water supply. 2 references, 7 figures.
Uncertainties affecting fund collection, management and final utilisation
International Nuclear Information System (INIS)
Soederberg, Olof
2006-01-01
The paper presents, on a general level, major uncertainties in financing systems aiming at providing secure funding for future costs for decommissioning. The perspective chosen is that of a fund collector/manager. The paper also contains a description of how these uncertainties are dealt within the Swedish financing system and particularly from the perspective of the Board of the Swedish Nuclear Waste Fund. It is concluded that existing uncertainties are a good reason not to postpone decommissioning activities to a distant future. This aspect is important also when countries have in place financing systems that have been constructed in order to be robust against identified uncertainties. (author)