Development of a Mobile Application for Building Energy Prediction Using Performance Prediction Model

Directory of Open Access Journals (Sweden)

Yu-Ri Kim

2016-03-01

Full Text Available Recently, the Korean government has enforced disclosure of building energy performance, so that such information can help owners and prospective buyers to make suitable investment plans. Such a building energy performance policy of the government makes it mandatory for the building owners to obtain engineering audits and thereby evaluate the energy performance levels of their buildings. However, to calculate energy performance levels (i.e., asset rating methodology, a qualified expert needs to have access to at least the full project documentation and/or conduct an on-site inspection of the buildings. Energy performance certification costs a lot of time and money. Moreover, the database of certified buildings is still actually quite small. A need, therefore, is increasing for a simplified and user-friendly energy performance prediction tool for non-specialists. Also, a database which allows building owners and users to compare best practices is required. In this regard, the current study developed a simplified performance prediction model through experimental design, energy simulations and ANOVA (analysis of variance. Furthermore, using the new prediction model, a related mobile application was also developed.

A fuzzy expert system for predicting the performance of switched reluctance motor

International Nuclear Information System (INIS)

Mirzaeian, B.; Moallem, M.; Lucas, Caro

2001-01-01

In this paper a fuzzy expert system for predicting the performance of a switched reluctance motor has been developed. The design vector consists of design parameters, and output performance variables are efficiency and torque ripple. An accurate analysis program based on Improved Magnetic Equivalent Circuit method has been used to generate the input-output data. These input-output data is used to produce the initial fuzzy rules for predicting the performance of Switched Reluctance Motor. The initial set of fuzzy rules with triangular membership functions has been devised using a table look-up scheme. The initial fuzzy rules have been optimized to a set of fuzzy rules with Gaussian membership functions using gradient descent training scheme. The performance prediction results for a 6/8, 4 kw, Switched Reluctance Motor shows good agreement with the results obtained from Improved Magnetic Equivalent Circuit method or Finite Element analysis. The developed fuzzy expert system can be used for fast prediction of motor performance in the optimal design process or on-line control schemes of Switched Reluctance motor

Mean streamline analysis for performance prediction of cross-flow fans

International Nuclear Information System (INIS)

Kim, Jae Won; Oh, Hyoung Woo

2004-01-01

This paper presents the mean streamline analysis using the empirical loss correlations for performance prediction of cross-flow fans. Comparison of overall performance predictions with test data of a cross-flow fan system with a simplified vortex wall scroll casing and with the published experimental characteristics for a cross-flow fan has been carried out to demonstrate the accuracy of the proposed method. Predicted performance curves by the present mean streamline analysis agree well with experimental data for two different cross-flow fans over the normal operating conditions. The prediction method presented herein can be used efficiently as a tool for the preliminary design and performance analysis of general-purpose cross-flow fans

Preliminary design and off-design performance analysis of an Organic Rankine Cycle for geothermal sources

International Nuclear Information System (INIS)

Hu, Dongshuai; Li, Saili; Zheng, Ya; Wang, Jiangfeng; Dai, Yiping

2015-01-01

Highlights: • A method for preliminary design and performance prediction is established. • Preliminary data of radial inflow turbine and plate heat exchanger are obtained. • Off-design performance curves of critical components are researched. • Performance maps in sliding pressure operation are illustrated. - Abstract: Geothermal fluid of 90 °C and 10 kg/s can be exploited together with oil in Huabei Oilfield of China. Organic Rankine Cycle is regarded as a reasonable method to utilize these geothermal sources. This study conducts a detailed design and off-design performance analysis based on the preliminary design of turbines and heat exchangers. The radial inflow turbine and plate heat exchanger are selected in this paper. Sliding pressure operation is applied in the simulation and three parameters are considered: geothermal fluid mass flow rate, geothermal fluid temperature and condensing pressure. The results indicate that in all considered conditions the designed radial inflow turbine has smooth off-design performance and no choke or supersonic flow are found at the nozzle and rotor exit. The lager geothermal fluid mass flow rate, the higher geothermal fluid temperature and the lower condensing pressure contribute to the increase of cycle efficiency and net power. Performance maps are illustrated to make system meet different load requirements especially when the geothermal fluid temperature and condensing pressure deviate from the design condition. This model can be used to provide basic data for future detailed design, and predict off-design performance in the initial design phase

Hyperformance: predicting high-speed performance of a b-double

CSIR Research Space (South Africa)

Berman, Robert J

2016-11-01

Full Text Available of the vehicles. The prediction model bridges that gap in the form of a light-weight methodology to predict the PBS performance of a new vehicle design given a set of vehicle input data. Such a model was developed for typical South African 9-axle B-double PBS...

Optimal design criteria - prediction vs. parameter estimation

Science.gov (United States)

Waldl, Helmut

2014-05-01

G-optimality is a popular design criterion for optimal prediction, it tries to minimize the kriging variance over the whole design region. A G-optimal design minimizes the maximum variance of all predicted values. If we use kriging methods for prediction it is self-evident to use the kriging variance as a measure of uncertainty for the estimates. Though the computation of the kriging variance and even more the computation of the empirical kriging variance is computationally very costly and finding the maximum kriging variance in high-dimensional regions can be time demanding such that we cannot really find the G-optimal design with nowadays available computer equipment in practice. We cannot always avoid this problem by using space-filling designs because small designs that minimize the empirical kriging variance are often non-space-filling. D-optimality is the design criterion related to parameter estimation. A D-optimal design maximizes the determinant of the information matrix of the estimates. D-optimality in terms of trend parameter estimation and D-optimality in terms of covariance parameter estimation yield basically different designs. The Pareto frontier of these two competing determinant criteria corresponds with designs that perform well under both criteria. Under certain conditions searching the G-optimal design on the above Pareto frontier yields almost as good results as searching the G-optimal design in the whole design region. In doing so the maximum of the empirical kriging variance has to be computed only a few times though. The method is demonstrated by means of a computer simulation experiment based on data provided by the Belgian institute Management Unit of the North Sea Mathematical Models (MUMM) that describe the evolution of inorganic and organic carbon and nutrients, phytoplankton, bacteria and zooplankton in the Southern Bight of the North Sea.

Proactive Supply Chain Performance Management with Predictive Analytics

Directory of Open Access Journals (Sweden)

Nenad Stefanovic

2014-01-01

Full Text Available Today’s business climate requires supply chains to be proactive rather than reactive, which demands a new approach that incorporates data mining predictive analytics. This paper introduces a predictive supply chain performance management model which combines process modelling, performance measurement, data mining models, and web portal technologies into a unique model. It presents the supply chain modelling approach based on the specialized metamodel which allows modelling of any supply chain configuration and at different level of details. The paper also presents the supply chain semantic business intelligence (BI model which encapsulates data sources and business rules and includes the data warehouse model with specific supply chain dimensions, measures, and KPIs (key performance indicators. Next, the paper describes two generic approaches for designing the KPI predictive data mining models based on the BI semantic model. KPI predictive models were trained and tested with a real-world data set. Finally, a specialized analytical web portal which offers collaborative performance monitoring and decision making is presented. The results show that these models give very accurate KPI projections and provide valuable insights into newly emerging trends, opportunities, and problems. This should lead to more intelligent, predictive, and responsive supply chains capable of adapting to future business environment.

Proactive supply chain performance management with predictive analytics.

Science.gov (United States)

Stefanovic, Nenad

2014-01-01

Today's business climate requires supply chains to be proactive rather than reactive, which demands a new approach that incorporates data mining predictive analytics. This paper introduces a predictive supply chain performance management model which combines process modelling, performance measurement, data mining models, and web portal technologies into a unique model. It presents the supply chain modelling approach based on the specialized metamodel which allows modelling of any supply chain configuration and at different level of details. The paper also presents the supply chain semantic business intelligence (BI) model which encapsulates data sources and business rules and includes the data warehouse model with specific supply chain dimensions, measures, and KPIs (key performance indicators). Next, the paper describes two generic approaches for designing the KPI predictive data mining models based on the BI semantic model. KPI predictive models were trained and tested with a real-world data set. Finally, a specialized analytical web portal which offers collaborative performance monitoring and decision making is presented. The results show that these models give very accurate KPI projections and provide valuable insights into newly emerging trends, opportunities, and problems. This should lead to more intelligent, predictive, and responsive supply chains capable of adapting to future business environment.

Proactive Supply Chain Performance Management with Predictive Analytics

Science.gov (United States)

Stefanovic, Nenad

2014-01-01

Today's business climate requires supply chains to be proactive rather than reactive, which demands a new approach that incorporates data mining predictive analytics. This paper introduces a predictive supply chain performance management model which combines process modelling, performance measurement, data mining models, and web portal technologies into a unique model. It presents the supply chain modelling approach based on the specialized metamodel which allows modelling of any supply chain configuration and at different level of details. The paper also presents the supply chain semantic business intelligence (BI) model which encapsulates data sources and business rules and includes the data warehouse model with specific supply chain dimensions, measures, and KPIs (key performance indicators). Next, the paper describes two generic approaches for designing the KPI predictive data mining models based on the BI semantic model. KPI predictive models were trained and tested with a real-world data set. Finally, a specialized analytical web portal which offers collaborative performance monitoring and decision making is presented. The results show that these models give very accurate KPI projections and provide valuable insights into newly emerging trends, opportunities, and problems. This should lead to more intelligent, predictive, and responsive supply chains capable of adapting to future business environment. PMID:25386605

Predicting Document Retrieval System Performance: An Expected Precision Measure.

Science.gov (United States)

Losee, Robert M., Jr.

1987-01-01

Describes an expected precision (EP) measure designed to predict document retrieval performance. Highlights include decision theoretic models; precision and recall as measures of system performance; EP graphs; relevance feedback; and computing the retrieval status value of a document for two models, the Binary Independent Model and the Two Poisson…

A Probabilistic Design Methodology for a Turboshaft Engine Overall Performance Analysis

Directory of Open Access Journals (Sweden)

Min Chen

2014-05-01

Full Text Available In reality, the cumulative effect of the many uncertainties in engine component performance may stack up to affect the engine overall performance. This paper aims to quantify the impact of uncertainty in engine component performance on the overall performance of a turboshaft engine based on Monte-Carlo probabilistic design method. A novel probabilistic model of turboshaft engine, consisting of a Monte-Carlo simulation generator, a traditional nonlinear turboshaft engine model, and a probability statistical model, was implemented to predict this impact. One of the fundamental results shown herein is that uncertainty in component performance has a significant impact on the engine overall performance prediction. This paper also shows that, taking into consideration the uncertainties in component performance, the turbine entry temperature and overall pressure ratio based on the probabilistic design method should increase by 0.76% and 8.33%, respectively, compared with the ones of deterministic design method. The comparison shows that the probabilistic approach provides a more credible and reliable way to assign the design space for a target engine overall performance.

Modelling the predictive performance of credit scoring

Directory of Open Access Journals (Sweden)

Shi-Wei Shen

2013-07-01

Research purpose: The purpose of this empirical paper was to examine the predictive performance of credit scoring systems in Taiwan. Motivation for the study: Corporate lending remains a major business line for financial institutions. However, in light of the recent global financial crises, it has become extremely important for financial institutions to implement rigorous means of assessing clients seeking access to credit facilities. Research design, approach and method: Using a data sample of 10 349 observations drawn between 1992 and 2010, logistic regression models were utilised to examine the predictive performance of credit scoring systems. Main findings: A test of Goodness of fit demonstrated that credit scoring models that incorporated the Taiwan Corporate Credit Risk Index (TCRI, micro- and also macroeconomic variables possessed greater predictive power. This suggests that macroeconomic variables do have explanatory power for default credit risk. Practical/managerial implications: The originality in the study was that three models were developed to predict corporate firms’ defaults based on different microeconomic and macroeconomic factors such as the TCRI, asset growth rates, stock index and gross domestic product. Contribution/value-add: The study utilises different goodness of fits and receiver operator characteristics during the examination of the robustness of the predictive power of these factors.

Daylight prediction techniques in energy design tools

Energy Technology Data Exchange (ETDEWEB)

Milne, M.; Zurick, J. [California Univ., Los Angeles, Dept. of Architecture, CA (United States)

1998-09-01

Four different whole-building energy design tool systems that calculate energy savings from daylighting and that display annual performance on an-hour-by-hour basis, have been tested. The nature of design tools, the sources of hourly outdoor illuminance data, the ways of predicting indoor illumination, the assumptions of each tool, and the resulting energy savings of the design tools tested are discussed. The tests were carried out with the essential criteria for evaluating whole-building daylighting and energy design tools in mind. These have been identified as user confidence, accuracy, response time, and the amount of detail. Results of the tests, all four of them run on a single elementary school classroom for the sake of comparability, were provided. 9 refs., 2 figs.

Multi performance option in direct displacement based design

Directory of Open Access Journals (Sweden)

Muljati Ima

2017-01-01

Full Text Available Compare to traditional method, direct displacement based design (DDBD offers the more rational design choice due to its compatibility with performance based design which is controlled by the targeted displacement in design. The objectives of this study are: 1 to explore the performance of DDBD for design Level-1, -2 and -3; 2 to determine the most appropriate design level based on material efficiency and damage risk; and 3 to verify the chosen design in order to check its performance under small-, moderate- and severe earthquake. As case study, it uses regular concrete frame structures consists of fourand eight-story with typical plan, located in low- and high-risk seismicity area. The study shows that design Level-2 (repairable damage is the most appropriate choice. Nonlinear time history analysis is run for each case study in order to verify their performance based on parameter: story drift, damage indices, and plastic mechanism. It can be concluded that DDBD performed very well in predicting seismic demand of the observed structures. Design Level-2 can be chosen as the most appropriate design level. Structures are in safe plastic mechanism under all level of seismicity although some plastic hinges formed at some unexpected locations.

Comparison of Simple Versus Performance-Based Fall Prediction Models

Directory of Open Access Journals (Sweden)

Shekhar K. Gadkaree BS

2015-05-01

Full Text Available Objective: To compare the predictive ability of standard falls prediction models based on physical performance assessments with more parsimonious prediction models based on self-reported data. Design: We developed a series of fall prediction models progressing in complexity and compared area under the receiver operating characteristic curve (AUC across models. Setting: National Health and Aging Trends Study (NHATS, which surveyed a nationally representative sample of Medicare enrollees (age ≥65 at baseline (Round 1: 2011-2012 and 1-year follow-up (Round 2: 2012-2013. Participants: In all, 6,056 community-dwelling individuals participated in Rounds 1 and 2 of NHATS. Measurements: Primary outcomes were 1-year incidence of “ any fall ” and “ recurrent falls .” Prediction models were compared and validated in development and validation sets, respectively. Results: A prediction model that included demographic information, self-reported problems with balance and coordination, and previous fall history was the most parsimonious model that optimized AUC for both any fall (AUC = 0.69, 95% confidence interval [CI] = [0.67, 0.71] and recurrent falls (AUC = 0.77, 95% CI = [0.74, 0.79] in the development set. Physical performance testing provided a marginal additional predictive value. Conclusion: A simple clinical prediction model that does not include physical performance testing could facilitate routine, widespread falls risk screening in the ambulatory care setting.

Performing Performance Design Anglonationally

DEFF Research Database (Denmark)

2016-01-01

Video recording of pecha kucha style bricolage aural enactment of an international version of performance design......Video recording of pecha kucha style bricolage aural enactment of an international version of performance design...

Integrated predictive modelling simulations of burning plasma experiment designs

International Nuclear Information System (INIS)

Bateman, Glenn; Onjun, Thawatchai; Kritz, Arnold H

2003-01-01

Models for the height of the pedestal at the edge of H-mode plasmas (Onjun T et al 2002 Phys. Plasmas 9 5018) are used together with the Multi-Mode core transport model (Bateman G et al 1998 Phys. Plasmas 5 1793) in the BALDUR integrated predictive modelling code to predict the performance of the ITER (Aymar A et al 2002 Plasma Phys. Control. Fusion 44 519), FIRE (Meade D M et al 2001 Fusion Technol. 39 336), and IGNITOR (Coppi B et al 2001 Nucl. Fusion 41 1253) fusion reactor designs. The simulation protocol used in this paper is tested by comparing predicted temperature and density profiles against experimental data from 33 H-mode discharges in the JET (Rebut P H et al 1985 Nucl. Fusion 25 1011) and DIII-D (Luxon J L et al 1985 Fusion Technol. 8 441) tokamaks. The sensitivities of the predictions are evaluated for the burning plasma experimental designs by using variations of the pedestal temperature model that are one standard deviation above and below the standard model. Simulations of the fusion reactor designs are carried out for scans in which the plasma density and auxiliary heating power are varied

A new modeling procedure for circuit design and performance prediction of evaporator coils using CO2 as refrigerant

International Nuclear Information System (INIS)

Larbi Bendaoud, Adlane; Ouzzane, Mohamed; Aidoun, Zine; Galanis, Nicolas

2010-01-01

The replacement of environmentally damaging synthetic refrigerants due to their ODP or GWI potential by natural refrigerants such as CO 2 is now up in the research agenda. Moreover, current energy supply concerns make of efficiency another first priority issue to dictate new stringent design criteria for industrial and commercial equipment. Heat exchangers are the most important components in refrigeration systems where they are used as evaporators or condensers and their design and operation have a considerable impact on overall system performance. Hence, it is important to better understand their thermal and hydrodynamic behaviour in order to improve their design and operation. Numerical simulation represents a very efficient tool for achieving this objective. In this paper, a new modeling approach, accounting for the heat transfer the hydrodynamics of the problem and intended to predict the dynamic behaviour of a refrigeration coil under dry conditions is proposed. A related FORTRAN program was developed, allowing the study of a large range of complex refrigerant circuit configurations. The equations describing these aspects are strongly coupled, and their decoupling is reached by using an original method of resolution. Circuits may have several inlets, outlets, bifurcations and feed one or several other tubes inlets. The coil was subdivided into several elementary control volumes and its analysis provided detailed information in X, Y and Z directions. Validation was performed with data from a CO 2 secondary refrigeration loop test bench built in CanmetENERGY Laboratories. These data were predicted satisfactorily over the operating range corresponding to refrigeration applications. Exemplary simulations were then performed on an evaporator typically employed in supermarkets, showing the effect of circuiting on operation and performance. Even though circuiting is common practice in refrigeration this simulation shows that care must be exercised in making the

Analysis of predicted and measured performance of an integrated compound parabolic concentrator (ICPC)

Energy Technology Data Exchange (ETDEWEB)

Winston, R.; O' Gallagher, J.J.; Muschaweck, J.; Mahoney, A.R.; Dudley, V.

1999-07-01

A variety of configurations of evacuated Integrated Compound Parabolic Concentrator (ICPC) tubes have been under development for many years. A particularly favorable optical design corresponds to the unit concentration limit for a fin CPC solution which is then coupled to a practical, thin, wedge-shaped absorber. Prototype collector modules using tubes with two different fin orientations (horizontal and vertical) have been fabricated and tested. Comprehensive measurements of the optical characteristics of the reflector and absorber have been used together with a detailed ray trace analysis to predict the optical performance characteristics of these designs. The observed performance agrees well with the predicted performance.

Integrated design of castings: effect of porosity on mechanical performance

International Nuclear Information System (INIS)

Hardin, R A; Beckermann, C

2012-01-01

Porosity can significantly reduce the strength and durability of castings in service. An integrated design approach has been developed where casting simulation is combined with mechanical performance simulations. Predictions of the porosity distribution from the casting process simulation are transferred to and used in stress and fatigue life simulations. Thus, the effect of casting quality on service performance can be evaluated. Results of a study are presented where the measured porosity distribution in cast steel specimens is transferred to an elasto-plastic finite-element stress analysis model. Methods are developed to locally reduce the mechanical properties according to the porosity present, without having to resolve individual pores. Plastic deformation is modeled using porous metal plasticity theory. The predictions are compared to tensile measurements performed on the specimens. The complex deformations and the reductions in the ductility of the specimens due to porosity are predicted well. The predicted stresses are transferred to a fatigue analysis code that takes the porosity distribution into account as well. The measured and predicted fatigue lives are also in good agreement. Finally, the results of a case study are presented that illustrate the utility of the present integrated approach in optimizing the design of a steel casting.

Development of Mitsubishi high thermal performance grid 1 - CFD applicability for thermal hydraulic design

International Nuclear Information System (INIS)

Ikeda, K.; Hoshi, M.

2001-01-01

Mitsubishi applied the Computational Fluid Dynamics (CFD) evaluation method for designing of the new lower pressure loss and higher DNB performance grid spacer. Reduction of pressure loss of the grid has been estimated by CFD. Also, CFD has been developed as a design tool to predict the coolant mixing ability of vane structures, that is to compare the relative peak spot temperatures around fuel rods at the same heat flux condition. These evaluations have been reflected to the new grid spacer design. The prototype grid was manufactured and some flow tests were performed to examine the thermal hydraulic performance, which were predicted by CFD. The experimental data of pressure loss was in good agreement with CFD prediction. The CFD prediction of flow behaviors at downstream of the mixing vanes was verified by detail cross-flow measurements at rod gaps by the rod LDV system. It is concluded that the applicability of the CFD evaluation method for the thermal hydraulic design of the grid is confirmed. (authors)

What predicts performance during clinical psychology training?

OpenAIRE

Scior, Katrina; Bradley, Caroline E; Potts, Henry W W; Woolf, Katherine; de C Williams, Amanda C

2013-01-01

Objectives While the question of who is likely to be selected for clinical psychology training has been studied, evidence on performance during training is scant. This study explored data from seven consecutive intakes of the UK's largest clinical psychology training course, aiming to identify what factors predict better or poorer outcomes. Design Longitudinal cross-sectional study using prospective and retrospective data. Method Characteristics at application were analysed in relation to a r...

A human capital predictive model for agent performance in contact centres

Directory of Open Access Journals (Sweden)

Chris Jacobs

2011-10-01

Research purpose: The primary focus of this article was to develop a theoretically derived human capital predictive model for agent performance in contact centres and Business Process Outsourcing (BPO based on a review of current empirical research literature. Motivation for the study: The study was motivated by the need for a human capital predictive model that can predict agent and overall business performance. Research design: A nonempirical (theoretical research paradigm was adopted for this study and more specifically a theory or model-building approach was followed. A systematic review of published empirical research articles (for the period 2000–2009 in scholarly search portals was performed. Main findings: Eight building blocks of the human capital predictive model for agent performance in contact centres were identified. Forty-two of the human capital contact centre related articles are detailed in this study. Key empirical findings suggest that person– environment fit, job demands-resources, human resources management practices, engagement, agent well-being, agent competence; turnover intention; and agent performance are related to contact centre performance. Practical/managerial implications: The human capital predictive model serves as an operational management model that has performance implications for agents and ultimately influences the contact centre’s overall business performance. Contribution/value-add: This research can contribute to the fields of human resource management (HRM, human capital and performance management within the contact centre and BPO environment.

Design and performance prediction of an adsorption heat pump with multi-cooling tubes

Energy Technology Data Exchange (ETDEWEB)

Wang, D.C.; Zhang, J.P. [College of Electromechanical Engineering, Qingdao University, Qingdao 266071 (China)

2009-05-15

Widespread application of adsorption heat pumps has been delayed not only by poor heat and mass transfer performance but also by low operating reliability because high vacuum must be maintained in the adsorption cooling system, especially in a water system. An adsorption cooling tube is a tube in which an adsorber, a condenser and an evaporator are all completely housed to construct a small scale adsorption cooling unit. In this work, an adsorption cooling tube and an adsorption heat pump with multi-cooling tubes are designed. A theoretical model is built to simulate the performance of the designed chiller. According to the results, the coefficient of performance and specific cooling power reach about 0.5 and 85 W/kg adsorbent, respectively, at the hot water temperature of 85 C. These results indicate that the designed heat pump in this work would provide a better choice if the operating reliability became crucial for an adsorption heat pump. (author)

Design and performance prediction of an adsorption heat pump with multi-cooling tubes

International Nuclear Information System (INIS)

Wang, D.C.; Zhang, J.P.

2009-01-01

Widespread application of adsorption heat pumps has been delayed not only by poor heat and mass transfer performance but also by low operating reliability because high vacuum must be maintained in the adsorption cooling system, especially in a water system. An adsorption cooling tube is a tube in which an adsorber, a condenser and an evaporator are all completely housed to construct a small scale adsorption cooling unit. In this work, an adsorption cooling tube and an adsorption heat pump with multi-cooling tubes are designed. A theoretical model is built to simulate the performance of the designed chiller. According to the results, the coefficient of performance and specific cooling power reach about 0.5 and 85 W/kg adsorbent, respectively, at the hot water temperature of 85 deg. C. These results indicate that the designed heat pump in this work would provide a better choice if the operating reliability became crucial for an adsorption heat pump.

Predicting Eight Grade Students' Equation Solving Performances via Concepts of Variable and Equality

Science.gov (United States)

Ertekin, Erhan

2017-01-01

This study focused on how two algebraic concepts- equality and variable- predicted 8th grade students' equation solving performance. In this study, predictive design as a correlational research design was used. Randomly selected 407 eight-grade students who were from the central districts of a city in the central region of Turkey participated in…

Predicting emergency diesel starting performance

International Nuclear Information System (INIS)

DeBey, T.M.

1989-01-01

The US Department of Energy effort to extend the operational lives of commercial nuclear power plants has examined methods for predicting the performance of specific equipment. This effort focuses on performance prediction as a means for reducing equipment surveillance, maintenance, and outages. Realizing these goals will result in nuclear plants that are more reliable, have lower maintenance costs, and have longer lives. This paper describes a monitoring system that has been developed to predict starting performance in emergency diesels. A prototype system has been built and tested on an engine at Sandia National Laboratories. 2 refs

Performance Aided Design

DEFF Research Database (Denmark)

Parigi, Dario

2014-01-01

paradigm where the increasing integration of parametric tools and performative analysis is changing the way we learn and design. The term Performance Aided Architectural Design (PAD) is proposed at the Master of Science of Architecture and Design at Aalborg University, with the aim of extending a tectonic...... tradition of architecture with computational tools, preparing the basis for the creation of the figure of a modern master builder, sitting at the boundary of the disciplines of architecture and engineering. Performance Aided Design focuses on the role of performative analysis, embedded tectonics......, and computational methods tools to trigger creativity and innovative understanding of relation between form material and a increasingly wide range of performances in architectural design. The ultimate goal is to pursue a design approach that aims at embracing rather than excluding the complexity implicit...

Evaluation on the model of performance predictions for on-line monitoring system for combined-cycle power plant

International Nuclear Information System (INIS)

Kim, Si Moon

2002-01-01

This paper presents the simulation model developed to predict design and off-design performance of an actual combined cycle power plant(S-Station in Korea), which would be running combined with on-line performance monitoring system in an on-line real-time fashion. The first step in thermal performance analysis is to build an accurate performance model of the power plant, in order to achieve this goal, GateCycle program has been employed in developing the model. This developed models predict design and off-design performance with a precision of one percent over a wide range of operating conditions so that on-line real-time performance monitoring can accurately establish both current performance and expected performance and also help the operator identify problems before they would be noticed

Predicting the performance of fingerprint similarity searching.

Science.gov (United States)

Vogt, Martin; Bajorath, Jürgen

2011-01-01

Fingerprints are bit string representations of molecular structure that typically encode structural fragments, topological features, or pharmacophore patterns. Various fingerprint designs are utilized in virtual screening and their search performance essentially depends on three parameters: the nature of the fingerprint, the active compounds serving as reference molecules, and the composition of the screening database. It is of considerable interest and practical relevance to predict the performance of fingerprint similarity searching. A quantitative assessment of the potential that a fingerprint search might successfully retrieve active compounds, if available in the screening database, would substantially help to select the type of fingerprint most suitable for a given search problem. The method presented herein utilizes concepts from information theory to relate the fingerprint feature distributions of reference compounds to screening libraries. If these feature distributions do not sufficiently differ, active database compounds that are similar to reference molecules cannot be retrieved because they disappear in the "background." By quantifying the difference in feature distribution using the Kullback-Leibler divergence and relating the divergence to compound recovery rates obtained for different benchmark classes, fingerprint search performance can be quantitatively predicted.

Map-Based Power-Split Strategy Design with Predictive Performance Optimization for Parallel Hybrid Electric Vehicles

Directory of Open Access Journals (Sweden)

Jixiang Fan

2015-09-01

Full Text Available In this paper, a map-based optimal energy management strategy is proposed to improve the consumption economy of a plug-in parallel hybrid electric vehicle. In the design of the maps, which provide both the torque split between engine and motor and the gear shift, not only the current vehicle speed and power demand, but also the optimality based on the predicted trajectory of vehicle dynamics are considered. To seek the optimality, the equivalent consumption, which trades off the fuel and electricity usages, is chosen as the cost function. Moreover, in order to decrease the model errors in the process of optimization conducted in the discrete time domain, the variational integrator is employed to calculate the evolution of the vehicle dynamics. To evaluate the proposed energy management strategy, the simulation results performed on a professional GT-Suit simulator are demonstrated and the comparison to a real-time optimization method is also given to show the advantage of the proposed off-line optimization approach.

Preliminary Axial Flow Turbine Design and Off-Design Performance Analysis Methods for Rotary Wing Aircraft Engines. Part 1; Validation

Science.gov (United States)

Chen, Shu-cheng, S.

2009-01-01

For the preliminary design and the off-design performance analysis of axial flow turbines, a pair of intermediate level-of-fidelity computer codes, TD2-2 (design; reference 1) and AXOD (off-design; reference 2), are being evaluated for use in turbine design and performance prediction of the modern high performance aircraft engines. TD2-2 employs a streamline curvature method for design, while AXOD approaches the flow analysis with an equal radius-height domain decomposition strategy. Both methods resolve only the flows in the annulus region while modeling the impact introduced by the blade rows. The mathematical formulations and derivations involved in both methods are documented in references 3, 4 for TD2-2) and in reference 5 (for AXOD). The focus of this paper is to discuss the fundamental issues of applicability and compatibility of the two codes as a pair of companion pieces, to perform preliminary design and off-design analysis for modern aircraft engine turbines. Two validation cases for the design and the off-design prediction using TD2-2 and AXOD conducted on two existing high efficiency turbines, developed and tested in the NASA/GE Energy Efficient Engine (GE-E3) Program, the High Pressure Turbine (HPT; two stages, air cooled) and the Low Pressure Turbine (LPT; five stages, un-cooled), are provided in support of the analysis and discussion presented in this paper.

Axisymmetric thrust-vectoring nozzle performance prediction

International Nuclear Information System (INIS)

Wilson, E. A.; Adler, D.; Bar-Yoseph, P.Z

1998-01-01

Throat-hinged geometrically variable converging-diverging thrust-vectoring nozzles directly affect the jet flow geometry and rotation angle at the nozzle exit as a function of the nozzle geometry, the nozzle pressure ratio and flight velocity. The consideration of nozzle divergence in the effective-geometric nozzle relation is theoretically considered here for the first time. In this study, an explicit calculation procedure is presented as a function of nozzle geometry at constant nozzle pressure ratio, zero velocity and altitude, and compared with experimental results in a civil thrust-vectoring scenario. This procedure may be used in dynamic thrust-vectoring nozzle design performance predictions or analysis for civil and military nozzles as well as in the definition of initial jet flow conditions in future numerical VSTOL/TV jet performance studies

Predicting sample size required for classification performance

Directory of Open Access Journals (Sweden)

Figueroa Rosa L

2012-02-01

Full Text Available Abstract Background Supervised learning methods need annotated data in order to generate efficient models. Annotated data, however, is a relatively scarce resource and can be expensive to obtain. For both passive and active learning methods, there is a need to estimate the size of the annotated sample required to reach a performance target. Methods We designed and implemented a method that fits an inverse power law model to points of a given learning curve created using a small annotated training set. Fitting is carried out using nonlinear weighted least squares optimization. The fitted model is then used to predict the classifier's performance and confidence interval for larger sample sizes. For evaluation, the nonlinear weighted curve fitting method was applied to a set of learning curves generated using clinical text and waveform classification tasks with active and passive sampling methods, and predictions were validated using standard goodness of fit measures. As control we used an un-weighted fitting method. Results A total of 568 models were fitted and the model predictions were compared with the observed performances. Depending on the data set and sampling method, it took between 80 to 560 annotated samples to achieve mean average and root mean squared error below 0.01. Results also show that our weighted fitting method outperformed the baseline un-weighted method (p Conclusions This paper describes a simple and effective sample size prediction algorithm that conducts weighted fitting of learning curves. The algorithm outperformed an un-weighted algorithm described in previous literature. It can help researchers determine annotation sample size for supervised machine learning.

Numerical simulation of turbulence flow in a Kaplan turbine -Evaluation on turbine performance prediction accuracy-

International Nuclear Information System (INIS)

Ko, P; Kurosawa, S

2014-01-01

The understanding and accurate prediction of the flow behaviour related to cavitation and pressure fluctuation in a Kaplan turbine are important to the design work enhancing the turbine performance including the elongation of the operation life span and the improvement of turbine efficiency. In this paper, high accuracy turbine and cavitation performance prediction method based on entire flow passage for a Kaplan turbine is presented and evaluated. Two-phase flow field is predicted by solving Reynolds-Averaged Navier-Stokes equations expressed by volume of fluid method tracking the free surface and combined with Reynolds Stress model. The growth and collapse of cavitation bubbles are modelled by the modified Rayleigh-Plesset equation. The prediction accuracy is evaluated by comparing with the model test results of Ns 400 Kaplan model turbine. As a result that the experimentally measured data including turbine efficiency, cavitation performance, and pressure fluctuation are accurately predicted. Furthermore, the cavitation occurrence on the runner blade surface and the influence to the hydraulic loss of the flow passage are discussed. Evaluated prediction method for the turbine flow and performance is introduced to facilitate the future design and research works on Kaplan type turbine

Numerical simulation of turbulence flow in a Kaplan turbine -Evaluation on turbine performance prediction accuracy-

Science.gov (United States)

Ko, P.; Kurosawa, S.

2014-03-01

The understanding and accurate prediction of the flow behaviour related to cavitation and pressure fluctuation in a Kaplan turbine are important to the design work enhancing the turbine performance including the elongation of the operation life span and the improvement of turbine efficiency. In this paper, high accuracy turbine and cavitation performance prediction method based on entire flow passage for a Kaplan turbine is presented and evaluated. Two-phase flow field is predicted by solving Reynolds-Averaged Navier-Stokes equations expressed by volume of fluid method tracking the free surface and combined with Reynolds Stress model. The growth and collapse of cavitation bubbles are modelled by the modified Rayleigh-Plesset equation. The prediction accuracy is evaluated by comparing with the model test results of Ns 400 Kaplan model turbine. As a result that the experimentally measured data including turbine efficiency, cavitation performance, and pressure fluctuation are accurately predicted. Furthermore, the cavitation occurrence on the runner blade surface and the influence to the hydraulic loss of the flow passage are discussed. Evaluated prediction method for the turbine flow and performance is introduced to facilitate the future design and research works on Kaplan type turbine.

Software Performs Complex Design Analysis

Science.gov (United States)

2008-01-01

Designers use computational fluid dynamics (CFD) to gain greater understanding of the fluid flow phenomena involved in components being designed. They also use finite element analysis (FEA) as a tool to help gain greater understanding of the structural response of components to loads, stresses and strains, and the prediction of failure modes. Automated CFD and FEA engineering design has centered on shape optimization, which has been hindered by two major problems: 1) inadequate shape parameterization algorithms, and 2) inadequate algorithms for CFD and FEA grid modification. Working with software engineers at Stennis Space Center, a NASA commercial partner, Optimal Solutions Software LLC, was able to utilize its revolutionary, one-of-a-kind arbitrary shape deformation (ASD) capability-a major advancement in solving these two aforementioned problems-to optimize the shapes of complex pipe components that transport highly sensitive fluids. The ASD technology solves the problem of inadequate shape parameterization algorithms by allowing the CFD designers to freely create their own shape parameters, therefore eliminating the restriction of only being able to use the computer-aided design (CAD) parameters. The problem of inadequate algorithms for CFD grid modification is solved by the fact that the new software performs a smooth volumetric deformation. This eliminates the extremely costly process of having to remesh the grid for every shape change desired. The program can perform a design change in a markedly reduced amount of time, a process that would traditionally involve the designer returning to the CAD model to reshape and then remesh the shapes, something that has been known to take hours, days-even weeks or months-depending upon the size of the model.

Predictive Measures of Locomotor Performance on an Unstable Walking Surface

Science.gov (United States)

Bloomberg, J. J.; Peters, B. T.; Mulavara, A. P.; Caldwell, E. E.; Batson, C. D.; De Dios, Y. E.; Gadd, N. E.; Goel, R.; Wood, S. J.; Cohen, H. S.;

Complexity factors and prediction of performance

International Nuclear Information System (INIS)

Braarud, Per Oeyvind

1998-03-01

Understanding of what makes a control room situation difficult to handle is important when studying operator performance, both with respect to prediction as well as improvement of the human performance. A factor analytic approach identified eight factors from operators' answers to an 39 item questionnaire about complexity of the operator's task in the control room. A Complexity Profiling Questionnaire was developed, based on the factor analytic results from the operators' conception of complexity. The validity of the identified complexity factors was studied by prediction of crew performance and prediction of plant performance from ratings of the complexity of scenarios. The scenarios were rated by both process experts and the operators participating in the scenarios, using the Complexity Profiling Questionnaire. The process experts' complexity ratings predicted both crew performance and plant performance, while the operators' rating predicted plant performance only. The results reported are from initial studies of complexity, and imply a promising potential for further studies of the concept. The approach used in the study as well as the reported results are discussed. A chapter about the structure of the conception of complexity, and a chapter about further research conclude the report. (author)

Selection of References in Wind Turbine Model Predictive Control Design

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Hovgaard, Tobias

2015-01-01

a model predictive controller for a wind turbine. One of the important aspects for a tracking control problem is how to setup the optimal reference tracking problem, as it might be relevant to track, e.g., the three concurrent references: optimal pitch angle, optimal rotational speed, and optimal power......Lowering the cost of energy is one of the major focus areas in the wind turbine industry. Recent research has indicated that wind turbine controllers based on model predictive control methods can be useful in obtaining this objective. A number of design considerations have to be made when designing....... The importance if the individual references differ depending in particular on the wind speed. In this paper we investigate the performance of a reference tracking model predictive controller with two different setups of the used optimal reference signals. The controllers are evaluated using an industrial high...

An approach for prediction of petroleum production facility performance considering Arctic influence factors

International Nuclear Information System (INIS)

Gao Xueli; Barabady, Javad; Markeset, Tore

2010-01-01

As the oil and gas (O and G) industry is increasing the focus on petroleum exploration and development in the Arctic region, it is becoming increasingly important to design exploration and production facilities to suit the local operating conditions. The cold and harsh climate, the long distance from customer and suppliers' markets, and the sensitive environment may have considerable influence on the choice of design solutions and production performance characteristics such as throughput capacity, reliability, availability, maintainability, and supportability (RAMS) as well as operational and maintenance activities. Due to this, data and information collected for similar systems used in a normal climate may not be suitable. Hence, it is important to study and develop methods for prediction of the production performance characteristics during the design and operation phases. The aim of this paper is to present an approach for prediction of the production performance for oil and gas production facilities considering influencing factors in Arctic conditions. The proportional repair model (PRM) is developed in order to predict repair rate in Arctic conditions. The model is based on the proportional hazard model (PHM). A simple case study is used to demonstrate how the proposed approach can be applied.

Dimensionless Numerical Approaches for the Performance Prediction of Marine Waterjet Propulsion Units

Directory of Open Access Journals (Sweden)

Marco Altosole

2012-01-01

Full Text Available One of the key issues at early design stage of a high-speed craft is the selection and the performance prediction of the propulsion system because at this stage only few information about the vessel are available. The objective of this work is precisely to provide the designer, in the case of waterjet propelled craft, with a simple and reliable calculation tool, able to predict the waterjet working points in design and off-design conditions, allowing to investigate several propulsive options during the ship design process. In the paper two original dimensionless numerical procedures, one referred to jet units for naval applications and the other more suitable for planing boats, are presented. The first procedure is based on a generalized performance map for mixed flow pumps, derived from the analysis of several waterjet pumps by applying similitude principles of the hydraulic machines. The second approach, validated by some comparisons with current waterjet installations, is based on a complete physical approach, from which a set of non-dimensional waterjet characteristics has been drawn by the authors. The presented application examples show the validity and the degree of accuracy of the proposed methodologies for the performance evaluation of waterjet propulsion systems.

Predictive Power of Machine Learning for Optimizing Solar Water Heater Performance: The Potential Application of High-Throughput Screening

Directory of Open Access Journals (Sweden)

Hao Li

2017-01-01

Full Text Available Predicting the performance of solar water heater (SWH is challenging due to the complexity of the system. Fortunately, knowledge-based machine learning can provide a fast and precise prediction method for SWH performance. With the predictive power of machine learning models, we can further solve a more challenging question: how to cost-effectively design a high-performance SWH? Here, we summarize our recent studies and propose a general framework of SWH design using a machine learning-based high-throughput screening (HTS method. Design of water-in-glass evacuated tube solar water heater (WGET-SWH is selected as a case study to show the potential application of machine learning-based HTS to the design and optimization of solar energy systems.

Protective design of critical infrastructure with high performance concretes

International Nuclear Information System (INIS)

Riedel, W.; Nöldgen, M.; Stolz, A.; Roller, C.

2012-01-01

Conclusions: High performance concrete constructions will allow innovative design solutions for critical infrastructures. Validation of engineering methods can reside on large and model scale experiments conducted on conventional concrete structures. New consistent impact experiments show extreme protection potential for UHPC. Modern FEM with concrete models and explicit rebar can model HPC and UHPC penetration resistance. SDOF and TDOF approaches are valuable design tools on local and global level. Combination of at least 2 out of 3 design methods FEM – XDOF- EXP allow reliable prediction and efficient innovative designs

Software Design Challenges in Time Series Prediction Systems Using Parallel Implementation of Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Narayanan Manikandan

2016-01-01

Full Text Available Software development life cycle has been characterized by destructive disconnects between activities like planning, analysis, design, and programming. Particularly software developed with prediction based results is always a big challenge for designers. Time series data forecasting like currency exchange, stock prices, and weather report are some of the areas where an extensive research is going on for the last three decades. In the initial days, the problems with financial analysis and prediction were solved by statistical models and methods. For the last two decades, a large number of Artificial Neural Networks based learning models have been proposed to solve the problems of financial data and get accurate results in prediction of the future trends and prices. This paper addressed some architectural design related issues for performance improvement through vectorising the strengths of multivariate econometric time series models and Artificial Neural Networks. It provides an adaptive approach for predicting exchange rates and it can be called hybrid methodology for predicting exchange rates. This framework is tested for finding the accuracy and performance of parallel algorithms used.

A multi-source, multi-study investigation of job performance prediction by political skill

DEFF Research Database (Denmark)

Blickle, G.; Ferris, G.R.; Munyon, T.P.

2011-01-01

-sectional and longitudinal designs, this research tested the hypotheses that employee political skill, measured from the perspective of employees' assessor A, will positively predict job performance rated by assessor B (i.e. Hypothesis 1a), and vice versa, that employee political skill measured by assessor B will predict...

Image processing system performance prediction and product quality evaluation

Science.gov (United States)

Stein, E. K.; Hammill, H. B. (Principal Investigator)

1976-01-01

The author has identified the following significant results. A new technique for image processing system performance prediction and product quality evaluation was developed. It was entirely objective, quantitative, and general, and should prove useful in system design and quality control. The technique and its application to determination of quality control procedures for the Earth Resources Technology Satellite NASA Data Processing Facility are described.

Predicting energy performance of a net-zero energy building: A statistical approach

International Nuclear Information System (INIS)

Kneifel, Joshua; Webb, David

2016-01-01

Highlights: • A regression model is applied to actual energy data from a net-zero energy building. • The model is validated through a rigorous statistical analysis. • Comparisons are made between model predictions and those of a physics-based model. • The model is a viable baseline for evaluating future models from the energy data. - Abstract: Performance-based building requirements have become more prevalent because it gives freedom in building design while still maintaining or exceeding the energy performance required by prescriptive-based requirements. In order to determine if building designs reach target energy efficiency improvements, it is necessary to estimate the energy performance of a building using predictive models and different weather conditions. Physics-based whole building energy simulation modeling is the most common approach. However, these physics-based models include underlying assumptions and require significant amounts of information in order to specify the input parameter values. An alternative approach to test the performance of a building is to develop a statistically derived predictive regression model using post-occupancy data that can accurately predict energy consumption and production based on a few common weather-based factors, thus requiring less information than simulation models. A regression model based on measured data should be able to predict energy performance of a building for a given day as long as the weather conditions are similar to those during the data collection time frame. This article uses data from the National Institute of Standards and Technology (NIST) Net-Zero Energy Residential Test Facility (NZERTF) to develop and validate a regression model to predict the energy performance of the NZERTF using two weather variables aggregated to the daily level, applies the model to estimate the energy performance of hypothetical NZERTFs located in different cities in the Mixed-Humid Climate Zone, and compares these

Dual throat NaK pump performance evaluation (conceptual design of prototype)

International Nuclear Information System (INIS)

Johnson, J.L.

1972-01-01

An evaluation of the performance of the dual throat NaK pump for the 5 Kwe Reactor TE System is discussed. Performance at nominal operating conditions and at startup conditions is predicted. The basis for selection of this pump design is presented. (U.S.)

Improved Hypersonic Inlet Performance Using Validated Strut Compression Designs

Science.gov (United States)

Bulman, M. J.; Stout, P. W.; Fernandez, R.

1997-01-01

Aerojet is currently executing two Strutjet propulsion contracts: one a Rocket Based Combined Cycle (RBCC) engine for a NASA-Marshall Space Flight Center (MSFC) Advanced Reusable Transportation Technology (ARTT) program, the second a Dual Mode Ram/Scramjet engine for a USAF Wright Laboratories Storable Fuel Scramjet Flow Path Concepts program. The engines employed in both programs operate at supersonic and low hypersonic speeds and use inlets employing forebody external and sidewall compression. Aerojet has developed and validated a successful design methodology applicable to these inlet types. Design features include an integrated vehicle forebody, external side compression struts, strut sidewall and throat bleed, a throat shock trap, and variable geometry internal contraction. Computation Fluid Dynamic (CFD) predictions and test data show these inlets allow substantially increased flow turning angles over other designs. These increased flow turning angles allow shorter and lighter engines than current designs, which in turn enables higher performing vehicles with broad operating characteristics. This paper describes the designs of two different inlets evaluated by the NASA-MSFC and USAF programs, discusses the results of wind tunnel tests performed by NASA-Lewis Research Center, and provides correlations of test data with CFD predictions. Parameters of interest include low Mach number starting capability, start sensitivity as a function of back pressure at various contraction ratios, flow turning angles, strut and throat bleed effects, and pressure recovery at various Mach numbers.

Explicit MPC design and performance-based tuning of an Adaptive Cruise Control Stop-&-Go

NARCIS (Netherlands)

Naus, G.J.L.; Ploeg, J.; Molengraft, M.J.G. van de; Steinbuch, M.

2008-01-01

This paper presents the synthesis, the implementation and the performance-based tuning of an Adaptive Cruise Control (ACC) Stop-&-Go (S&G) design. A Model Predictive Control (MPC) framework is adopted to design the controller. Performance of the controller is evaluated, distinguishing between

Evolution of property predictability during conceptual design

DEFF Research Database (Denmark)

Salonen, Mikko; Hansen, Claus Thorp; Perttula, Matti

2005-01-01

of design alternatives, and identify the alternative which properties are best predicted to fulfil the requirements. The objective of this paper is to study the evolution of property predictability during the early phases of design in a case study context, and reflect on the implications this may have......A product is designed with the purpose of possessing certain properties, which are prescribed as requirements in the design specification. It is a common understanding that early design work and the resulting selected design concept have a significant impact on the subsequent phases of the design...... process and on the properties of the obtained design result. However, during the early phases of design every decision and choice of solution is based on incomplete information. The nature of early design work is to formulate the design problem based on an interpretation of a need, to generate a set...

Building Predictive Human Performance Models of Skill Acquisition in a Data Entry Task

National Research Council Canada - National Science Library

Fu, Wai-Tat; Gonzalez, Cleotilde; Healy, Alice F; Kole, James A; Bourne, Jr., Lyle E

2006-01-01

.... Since data entry is a central component in most human-machine interaction, a predictive model of performance will provide useful information that informs interface design and effectiveness of training...

Design and performance of an analysis-by-synthesis class of predictive speech coders

Science.gov (United States)

Rose, Richard C.; Barnwell, Thomas P., III

1990-01-01

The performance of a broad class of analysis-by-synthesis linear predictive speech coders is quantified experimentally. The class of coders includes a number of well-known techniques as well as a very large number of speech coders which have not been named or studied. A general formulation for deriving the parametric representation used in all of the coders in the class is presented. A new coder, named the self-excited vocoder, is discussed because of its good performance with low complexity, and because of the insight this coder gives to analysis-by-synthesis coders in general. The results of a study comparing the performances of different members of this class are presented. The study takes the form of a series of formal subjective and objective speech quality tests performed on selected coders. The results of this study lead to some interesting and important observations concerning the controlling parameters for analysis-by-synthesis speech coders.

Adding propensity scores to pure prediction models fails to improve predictive performance

Directory of Open Access Journals (Sweden)

Amy S. Nowacki

2013-08-01

Full Text Available Background. Propensity score usage seems to be growing in popularity leading researchers to question the possible role of propensity scores in prediction modeling, despite the lack of a theoretical rationale. It is suspected that such requests are due to the lack of differentiation regarding the goals of predictive modeling versus causal inference modeling. Therefore, the purpose of this study is to formally examine the effect of propensity scores on predictive performance. Our hypothesis is that a multivariable regression model that adjusts for all covariates will perform as well as or better than those models utilizing propensity scores with respect to model discrimination and calibration.Methods. The most commonly encountered statistical scenarios for medical prediction (logistic and proportional hazards regression were used to investigate this research question. Random cross-validation was performed 500 times to correct for optimism. The multivariable regression models adjusting for all covariates were compared with models that included adjustment for or weighting with the propensity scores. The methods were compared based on three predictive performance measures: (1 concordance indices; (2 Brier scores; and (3 calibration curves.Results. Multivariable models adjusting for all covariates had the highest average concordance index, the lowest average Brier score, and the best calibration. Propensity score adjustment and inverse probability weighting models without adjustment for all covariates performed worse than full models and failed to improve predictive performance with full covariate adjustment.Conclusion. Propensity score techniques did not improve prediction performance measures beyond multivariable adjustment. Propensity scores are not recommended if the analytical goal is pure prediction modeling.

Performance Design

DEFF Research Database (Denmark)

Svabo, Connie

Contribution to conference: Art and Presence The emerging field of Performance Design is unfolded as a bastard form of research/art/design/practice, with shapeshifting, monstruous, hybrid and transformational qualities. The potential for presencing, which emerges out of momentarily transgressing...

Performative Urban Design

DEFF Research Database (Denmark)

Performative Urban Design seeks to identify emerging trends in urban design as they are reflected in the city's architecture and spatial design. A “cultural grafting” of the inner city is taking place; architecture and art are playing a crucial, catalytic role in urban development. On the one hand...... these issues through three perspectives: •Sense Architecture; •Place-Making; and •Urban Catalysts. The articles in this volume identify relevant theoretical positions within architecture, art, and urban strategies while demonstrating relevant concepts and methodological approaches drawn from practical......, this development has been rooted in massive investments in “corporate architecture.” On the other, cities themselves have invested heavily in new cultural centers and performative urban spaces that can fulfil the growing desire for entertainment and culture. The anthology Performative Urban Design addresses...

The Real World Significance of Performance Prediction

Science.gov (United States)

Pardos, Zachary A.; Wang, Qing Yang; Trivedi, Shubhendu

2012-01-01

In recent years, the educational data mining and user modeling communities have been aggressively introducing models for predicting student performance on external measures such as standardized tests as well as within-tutor performance. While these models have brought statistically reliable improvement to performance prediction, the real world…

Designing Closed-Loop Brain-Machine Interfaces Using Model Predictive Control

Directory of Open Access Journals (Sweden)

Gautam Kumar

2016-06-01

Full Text Available Brain-machine interfaces (BMIs are broadly defined as systems that establish direct communications between living brain tissue and external devices, such as artificial arms. By sensing and interpreting neuronal activities to actuate an external device, BMI-based neuroprostheses hold great promise in rehabilitating motor disabled subjects, such as amputees. In this paper, we develop a control-theoretic analysis of a BMI-based neuroprosthetic system for voluntary single joint reaching task in the absence of visual feedback. Using synthetic data obtained through the simulation of an experimentally validated psycho-physiological cortical circuit model, both the Wiener filter and the Kalman filter based linear decoders are developed. We analyze the performance of both decoders in the presence and in the absence of natural proprioceptive feedback information. By performing simulations, we show that the performance of both decoders degrades significantly in the absence of the natural proprioception. To recover the performance of these decoders, we propose two problems, namely tracking the desired position trajectory and tracking the firing rate trajectory of neurons which encode the proprioception, in the model predictive control framework to design optimal artificial sensory feedback. Our results indicate that while the position trajectory based design can only recover the position and velocity trajectories, the firing rate trajectory based design can recover the performance of the motor task along with the recovery of firing rates in other cortical regions. Finally, we extend our design by incorporating a network of spiking neurons and designing artificial sensory feedback in the form of a charged balanced biphasic stimulating current.

A Free Wake Numerical Simulation for Darrieus Vertical Axis Wind Turbine Performance Prediction

Science.gov (United States)

Belu, Radian

2010-11-01

In the last four decades, several aerodynamic prediction models have been formulated for the Darrieus wind turbine performances and characteristics. We can identified two families: stream-tube and vortex. The paper presents a simplified numerical techniques for simulating vertical axis wind turbine flow, based on the lifting line theory and a free vortex wake model, including dynamic stall effects for predicting the performances of a 3-D vertical axis wind turbine. A vortex model is used in which the wake is composed of trailing stream-wise and shedding span-wise vortices, whose strengths are equal to the change in the bound vortex strength as required by the Helmholz and Kelvin theorems. Performance parameters are computed by application of the Biot-Savart law along with the Kutta-Jukowski theorem and a semi-empirical stall model. We tested the developed model with an adaptation of the earlier multiple stream-tube performance prediction model for the Darrieus turbines. Predictions by using our method are shown to compare favorably with existing experimental data and the outputs of other numerical models. The method can predict accurately the local and global performances of a vertical axis wind turbine, and can be used in the design and optimization of wind turbines for built environment applications.

Performance Prediction of Centrifugal Compressor for Drop-In Testing Using Low Global Warming Potential Alternative Refrigerants and Performance Test Codes

Directory of Open Access Journals (Sweden)

Joo Hoon Park

2017-12-01

Full Text Available As environmental regulations to stall global warming are strengthened around the world, studies using newly developed low global warming potential (GWP alternative refrigerants are increasing. In this study, substitute refrigerants, R-1234ze (E and R-1233zd (E, were used in the centrifugal compressor of an R-134a 2-stage centrifugal chiller with a fixed rotational speed. Performance predictions and thermodynamic analyses of the centrifugal compressor for drop-in testing were performed. A performance prediction method based on the existing ASME PTC-10 performance test code was proposed. The proposed method yielded the expected operating area and operating point of the centrifugal compressor with alternative refrigerants. The thermodynamic performance of the first and second stages of the centrifugal compressor was calculated as the polytropic state. To verify the suitability of the proposed method, the drop-in test results of the two alternative refrigerants were compared. The predicted operating range based on the permissible deviation of ASME PTC-10 confirmed that the temperature difference was very small at the same efficiency. Because the drop-in test of R-1234ze (E was performed within the expected operating range, the centrifugal compressor using R-1234ze (E is considered well predicted. However, the predictions of the operating point and operating range of R-1233zd (E were lower than those of the drop-in test. The proposed performance prediction method will assist in understanding thermodynamic performance at the expected operating point and operating area of a centrifugal compressor using alternative gases based on limited design and structure information.

Hybrid Corporate Performance Prediction Model Considering Technical Capability

Directory of Open Access Journals (Sweden)

Joonhyuck Lee

2016-07-01

Full Text Available Many studies have tried to predict corporate performance and stock prices to enhance investment profitability using qualitative approaches such as the Delphi method. However, developments in data processing technology and machine-learning algorithms have resulted in efforts to develop quantitative prediction models in various managerial subject areas. We propose a quantitative corporate performance prediction model that applies the support vector regression (SVR algorithm to solve the problem of the overfitting of training data and can be applied to regression problems. The proposed model optimizes the SVR training parameters based on the training data, using the genetic algorithm to achieve sustainable predictability in changeable markets and managerial environments. Technology-intensive companies represent an increasing share of the total economy. The performance and stock prices of these companies are affected by their financial standing and their technological capabilities. Therefore, we apply both financial indicators and technical indicators to establish the proposed prediction model. Here, we use time series data, including financial, patent, and corporate performance information of 44 electronic and IT companies. Then, we predict the performance of these companies as an empirical verification of the prediction performance of the proposed model.

Performance Prediction Toolkit

Energy Technology Data Exchange (ETDEWEB)

2017-09-25

The Performance Prediction Toolkit (PPT), is a scalable co-design tool that contains the hardware and middle-ware models, which accept proxy applications as input in runtime prediction. PPT relies on Simian, a parallel discrete event simulation engine in Python or Lua, that uses the process concept, where each computing unit (host, node, core) is a Simian entity. Processes perform their task through message exchanges to remain active, sleep, wake-up, begin and end. The PPT hardware model of a compute core (such as a Haswell core) consists of a set of parameters, such as clock speed, memory hierarchy levels, their respective sizes, cache-lines, access times for different cache levels, average cycle counts of ALU operations, etc. These parameters are ideally read off a spec sheet or are learned using regression models learned from hardware counters (PAPI) data. The compute core model offers an API to the software model, a function called time_compute(), which takes as input a tasklist. A tasklist is an unordered set of ALU, and other CPU-type operations (in particular virtual memory loads and stores). The PPT application model mimics the loop structure of the application and replaces the computational kernels with a call to the hardware model's time_compute() function giving tasklists as input that model the compute kernel. A PPT application model thus consists of tasklists representing kernels and the high-er level loop structure that we like to think of as pseudo code. The key challenge for the hardware model's time_compute-function is to translate virtual memory accesses into actual cache hierarchy level hits and misses.PPT also contains another CPU core level hardware model, Analytical Memory Model (AMM). The AMM solves this challenge soundly, where our previous alternatives explicitly include the L1,L2,L3 hit-rates as inputs to the tasklists. Explicit hit-rates inevitably only reflect the application modeler's best guess, perhaps informed by a few

Ab-initio conformational epitope structure prediction using genetic algorithm and SVM for vaccine design.

Science.gov (United States)

Moghram, Basem Ameen; Nabil, Emad; Badr, Amr

2018-01-01

T-cell epitope structure identification is a significant challenging immunoinformatic problem within epitope-based vaccine design. Epitopes or antigenic peptides are a set of amino acids that bind with the Major Histocompatibility Complex (MHC) molecules. The aim of this process is presented by Antigen Presenting Cells to be inspected by T-cells. MHC-molecule-binding epitopes are responsible for triggering the immune response to antigens. The epitope's three-dimensional (3D) molecular structure (i.e., tertiary structure) reflects its proper function. Therefore, the identification of MHC class-II epitopes structure is a significant step towards epitope-based vaccine design and understanding of the immune system. In this paper, we propose a new technique using a Genetic Algorithm for Predicting the Epitope Structure (GAPES), to predict the structure of MHC class-II epitopes based on their sequence. The proposed Elitist-based genetic algorithm for predicting the epitope's tertiary structure is based on Ab-Initio Empirical Conformational Energy Program for Peptides (ECEPP) Force Field Model. The developed secondary structure prediction technique relies on Ramachandran Plot. We used two alignment algorithms: the ROSS alignment and TM-Score alignment. We applied four different alignment approaches to calculate the similarity scores of the dataset under test. We utilized the support vector machine (SVM) classifier as an evaluation of the prediction performance. The prediction accuracy and the Area Under Receiver Operating Characteristic (ROC) Curve (AUC) were calculated as measures of performance. The calculations are performed on twelve similarity-reduced datasets of the Immune Epitope Data Base (IEDB) and a large dataset of peptide-binding affinities to HLA-DRB1*0101. The results showed that GAPES was reliable and very accurate. We achieved an average prediction accuracy of 93.50% and an average AUC of 0.974 in the IEDB dataset. Also, we achieved an accuracy of 95

Methodology for Designing Models Predicting Success of Infertility Treatment

OpenAIRE

Alireza Zarinara; Mohammad Mahdi Akhondi; Hojjat Zeraati; Koorsh Kamali; Kazem Mohammad

2016-01-01

Abstract Background: The prediction models for infertility treatment success have presented since 25 years ago. There are scientific principles for designing and applying the prediction models that is also used to predict the success rate of infertility treatment. The purpose of this study is to provide basic principles for designing the model to predic infertility treatment success. Materials and Methods: In this paper, the principles for developing predictive models are explained and...

The GlueX central drift chamber: Design and performance

International Nuclear Information System (INIS)

Van Haarlem, Y.; Meyer, C.A.; Barbosa, F.; Dey, B.; Lawrence, D.; Razmyslovich, V.; Smith, E.; Visser, G.; Whitlatch, T.; Wilkin, G.; Zihlmann, B.

2010-01-01

Tests and studies concerning the design and performance of the GlueX Central Drift Chamber (CDC) are presented. A full-scale prototype was built to test and steer the mechanical and electronic design. Small scale prototypes were constructed to test for sagging and to do timing and resolution studies of the detector. These studies were used to choose the gas mixture and to program a Monte Carlo simulation that can predict the detector response in an external magnetic field. Particle identification and charge division possibilities were also investigated.

Designing high-Performance layered thermoelectric materials through orbital engineering

DEFF Research Database (Denmark)

Zhang, Jiawei; Song, Lirong; Madsen, Georg K. H.

2016-01-01

Thermoelectric technology, which possesses potential application in recycling industrial waste heat as energy, calls for novel high-performance materials. The systematic exploration of novel thermoelectric materials with excellent electronic transport properties is severely hindered by limited...... insight into the underlying bonding orbitals of atomic structures. Here we propose a simple yet successful strategy to discover and design high-performance layered thermoelectric materials through minimizing the crystal field splitting energy of orbitals to realize high orbital degeneracy. The approach...... naturally leads to design maps for optimizing the thermoelectric power factor through forming solid solutions and biaxial strain. Using this approach, we predict a series of potential thermoelectric candidates from layered CaAl2Si2-type Zintl compounds. Several of them contain nontoxic, low-cost and earth...

Design of JMTR high-performance fuel element

International Nuclear Information System (INIS)

Sakurai, Fumio; Shimakawa, Satoshi; Komori, Yoshihiro; Tsuchihashi, Keiichiro; Kaminaga, Fumito

1999-01-01

For test and research reactors, the core conversion to low-enriched uranium fuel is required from the viewpoint of non-proliferation of nuclear weapon material. Improvements of core performance are also required in order to respond to recent advanced utilization needs. In order to meet both requirements, a high-performance fuel element of high uranium density with Cd wires as burnable absorbers was adopted for JMTR core conversion to low-enriched uranium fuel. From the result of examination of an adaptability of a few group constants generated by a conventional transport-theory calculation with an isotropic scattering approximation to a few group diffusion-theory core calculation for design of the JMTR high-performance fuel element, it was clear that the depletion of Cd wires was not able to be predicted accurately using group constants generated by the conventional method. Therefore, a new generation method of a few group constants in consideration of an incident neutron spectrum at Cd wire was developed. As the result, the most suitable high-performance fuel element for JMTR was designed successfully, and that allowed extension of operation duration without refueling to almost twice as long and offer of irradiation field with constant neutron flux. (author)

Room design for high-performance electron microscopy

International Nuclear Information System (INIS)

Muller, David A.; Kirkland, Earl J.; Thomas, Malcolm G.; Grazul, John L.; Fitting, Lena; Weyland, Matthew

2006-01-01

Aberration correctors correct aberrations, not instabilities. Rather, as spatial resolution improves, a microscope's sensitivity to room environment becomes more noticeable, not less. Room design is now an essential part of the microscope installation process. Previously ignorable annoyances like computer fans, desk lamps and that chiller in the service corridor now may become the limiting factors in the microscopes performance. We discuss methods to quantitatively characterize the instrument's response to magnetic, mechanical, acoustical and thermal disturbances and thus predict the limits that the environment places on imaging and spectroscopy

Exploring the motivation jungle: Predicting performance on a novel task by investigating constructs from different motivation perspectives in tandem

NARCIS (Netherlands)

Nuland, H.J.C. van; Dusseldorp, E.; Martens, R.L.; Boekaerts, M.

2010-01-01

Different theoretical viewpoints on motivation make it hard to decide which model has the best potential to provide valid predictions on classroom performance. This study was designed to explore motivation constructs derived from different motivation perspectives that predict performance on a novel

Method for simulating predictive control of building systems operation in the early stages of building design

DEFF Research Database (Denmark)

Petersen, Steffen; Svendsen, Svend

2011-01-01

A method for simulating predictive control of building systems operation in the early stages of building design is presented. The method uses building simulation based on weather forecasts to predict whether there is a future heating or cooling requirement. This information enables the thermal...... control systems of the building to respond proactively to keep the operational temperature within the thermal comfort range with the minimum use of energy. The method is implemented in an existing building simulation tool designed to inform decisions in the early stages of building design through...... parametric analysis. This enables building designers to predict the performance of the method and include it as a part of the solution space. The method furthermore facilitates the task of configuring appropriate building systems control schemes in the tool, and it eliminates time consuming manual...

Design and performance analysis of gas and liquid radial turbines

Science.gov (United States)

Tan, Xu

In the first part of the research, pumps running in reverse as turbines are studied. This work uses experimental data of wide range of pumps representing the centrifugal pumps' configurations in terms of specific speed. Based on specific speed and specific diameter an accurate correlation is developed to predict the performances at best efficiency point of the centrifugal pump in its turbine mode operation. The proposed prediction method yields very good results to date compared to previous such attempts. The present method is compared to nine previous methods found in the literature. The comparison results show that the method proposed in this paper is the most accurate. The proposed method can be further complemented and supplemented by more future tests to increase its accuracy. The proposed method is meaningful because it is based both specific speed and specific diameter. The second part of the research is focused on the design and analysis of the radial gas turbine. The specification of the turbine is obtained from the solar biogas hybrid system. The system is theoretically analyzed and constructed based on the purchased compressor. Theoretical analysis results in a specification of 100lb/min, 900ºC inlet total temperature and 1.575atm inlet total pressure. 1-D and 3-D geometry of the rotor is generated based on Aungier's method. 1-D loss model analysis and 3-D CFD simulations are performed to examine the performances of the rotor. The total-to-total efficiency of the rotor is more than 90%. With the help of CFD analysis, modifications on the preliminary design obtained optimized aerodynamic performances. At last, the theoretical performance analysis on the hybrid system is performed with the designed turbine.

Prediction of Hydraulic Performance of a Scaled-Down Model of SMART Reactor Coolant Pump

Energy Technology Data Exchange (ETDEWEB)

Kwon, Sun Guk; Park, Jin Seok; Yu, Je Yong; Lee, Won Jae [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2010-08-15

An analysis was conducted to predict the hydraulic performance of a reactor coolant pump (RCP) of SMART at the off-design as well as design points. In order to reduce the analysis time efficiently, a single passage containing an impeller and a diffuser was considered as the computational domain. A stage scheme was used to perform a circumferential averaging of the flux on the impeller-diffuser interface. The pressure difference between the inlet and outlet of the pump was determined and was used to compute the head, efficiency, and break horse power (BHP) of a scaled-down model under conditions of steady-state incompressible flow. The predicted curves of the hydraulic performance of an RCP were similar to the typical characteristic curves of a conventional mixed-flow pump. The complex internal fluid flow of a pump, including the internal recirculation loss due to reverse flow, was observed at a low flow rate.

In-Service Design and Performance Prediction of Advanced Fusion Material Systems by Computational Modeling and Simulation

International Nuclear Information System (INIS)

G. R. Odette; G. E. Lucas

2005-01-01

This final report on ''In-Service Design and Performance Prediction of Advanced Fusion Material Systems by Computational Modeling and Simulation'' (DE-FG03-01ER54632) consists of a series of summaries of work that has been published, or presented at meetings, or both. It briefly describes results on the following topics: (1) A Transport and Fate Model for Helium and Helium Management; (2) Atomistic Studies of Point Defect Energetics, Dynamics and Interactions; (3) Multiscale Modeling of Fracture consisting of: (3a) A Micromechanical Model of the Master Curve (MC) Universal Fracture Toughness-Temperature Curve Relation, KJc(T - To), (3b) An Embrittlement DTo Prediction Model for the Irradiation Hardening Dominated Regime, (3c) Non-hardening Irradiation Assisted Thermal and Helium Embrittlement of 8Cr Tempered Martensitic Steels: Compilation and Analysis of Existing Data, (3d) A Model for the KJc(T) of a High Strength NFA MA957, (3e) Cracked Body Size and Geometry Effects of Measured and Effective Fracture Toughness-Model Based MC and To Evaluations of F82H and Eurofer 97, (3f) Size and Geometry Effects on the Effective Toughness of Cracked Fusion Structures; (4) Modeling the Multiscale Mechanics of Flow Localization-Ductility Loss in Irradiation Damaged BCC Alloys; and (5) A Universal Relation Between Indentation Hardness and True Stress-Strain Constitutive Behavior. Further details can be found in the cited references or presentations that generally can be accessed on the internet, or provided upon request to the authors. Finally, it is noted that this effort was integrated with our base program in fusion materials, also funded by the DOE OFES

Real-time Tsunami Inundation Prediction Using High Performance Computers

Science.gov (United States)

Oishi, Y.; Imamura, F.; Sugawara, D.

2014-12-01

Recently off-shore tsunami observation stations based on cabled ocean bottom pressure gauges are actively being deployed especially in Japan. These cabled systems are designed to provide real-time tsunami data before tsunamis reach coastlines for disaster mitigation purposes. To receive real benefits of these observations, real-time analysis techniques to make an effective use of these data are necessary. A representative study was made by Tsushima et al. (2009) that proposed a method to provide instant tsunami source prediction based on achieving tsunami waveform data. As time passes, the prediction is improved by using updated waveform data. After a tsunami source is predicted, tsunami waveforms are synthesized from pre-computed tsunami Green functions of linear long wave equations. Tsushima et al. (2014) updated the method by combining the tsunami waveform inversion with an instant inversion of coseismic crustal deformation and improved the prediction accuracy and speed in the early stages. For disaster mitigation purposes, real-time predictions of tsunami inundation are also important. In this study, we discuss the possibility of real-time tsunami inundation predictions, which require faster-than-real-time tsunami inundation simulation in addition to instant tsunami source analysis. Although the computational amount is large to solve non-linear shallow water equations for inundation predictions, it has become executable through the recent developments of high performance computing technologies. We conducted parallel computations of tsunami inundation and achieved 6.0 TFLOPS by using 19,000 CPU cores. We employed a leap-frog finite difference method with nested staggered grids of which resolution range from 405 m to 5 m. The resolution ratio of each nested domain was 1/3. Total number of grid points were 13 million, and the time step was 0.1 seconds. Tsunami sources of 2011 Tohoku-oki earthquake were tested. The inundation prediction up to 2 hours after the

Predicting failing performance on a standardized patient clinical performance examination: the importance of communication and professionalism skills deficits.

Science.gov (United States)

Chang, Anna; Boscardin, Christy; Chou, Calvin L; Loeser, Helen; Hauer, Karen E

2009-10-01

The purpose is to determine which assessment measures identify medical students at risk of failing a clinical performance examination (CPX). Retrospective case-control, multiyear design, contingency table analysis, n = 149. We identified two predictors of CPX failure in patient-physician interaction skills: low clerkship ratings (odds ratio 1.79, P = .008) and student progress review for communication or professionalism concerns (odds ratio 2.64, P = .002). No assessments predicted CPX failure in clinical skills. Performance concerns in communication and professionalism identify students at risk of failing the patient-physician interaction portion of a CPX. This correlation suggests that both faculty and standardized patients can detect noncognitive traits predictive of failing performance. Early identification of these students may allow for development of a structured supplemental curriculum with increased opportunities for practice and feedback. The lack of predictors in the clinical skills portion suggests limited faculty observation or feedback.

The Global Precipitation Measurement (GPM Spacecraft Power System Design and Orbital Performance

Directory of Open Access Journals (Sweden)

Dakermanji George

2017-01-01

The paper describes the power system design details, its performance to date and the lithium ion battery model that was developed for use in the energy balance analysis and is being used to predict the on-orbit health of the battery.

Neighborhood Integration and Connectivity Predict Cognitive Performance and Decline

Directory of Open Access Journals (Sweden)

Amber Watts PhD

2015-08-01

Full Text Available Objective: Neighborhood characteristics may be important for promoting walking, but little research has focused on older adults, especially those with cognitive impairment. We evaluated the role of neighborhood characteristics on cognitive function and decline over a 2-year period adjusting for measures of walking. Method: In a study of 64 older adults with and without mild Alzheimer’s disease (AD, we evaluated neighborhood integration and connectivity using geographical information systems data and space syntax analysis. In multiple regression analyses, we used these characteristics to predict 2-year declines in factor analytically derived cognitive scores (attention, verbal memory, mental status adjusting for age, sex, education, and self-reported walking. Results : Neighborhood integration and connectivity predicted cognitive performance at baseline, and changes in cognitive performance over 2 years. The relationships between neighborhood characteristics and cognitive performance were not fully explained by self-reported walking. Discussion : Clearer definitions of specific neighborhood characteristics associated with walkability are needed to better understand the mechanisms by which neighborhoods may impact cognitive outcomes. These results have implications for measuring neighborhood characteristics, design and maintenance of living spaces, and interventions to increase walking among older adults. We offer suggestions for future research measuring neighborhood characteristics and cognitive function.

Modification in the FUDA computer code to predict fuel performance at high burnup

Energy Technology Data Exchange (ETDEWEB)

Das, M; Arunakumar, B V; Prasad, P N [Nuclear Power Corp., Mumbai (India)

1997-08-01

The computer code FUDA (FUel Design Analysis) participated in the blind exercises organized by the IAEA CRP (Co-ordinated Research Programme) on FUMEX (Fuel Modelling at Extended Burnup). While the code prediction compared well with the experiments at Halden under various parametric and operating conditions, the fission gas release and fission gas pressure were found to be slightly over-predicted, particularly at high burnups. In view of the results of 6 FUMEX cases, the main models and submodels of the code were reviewed and necessary improvements were made. The new version of the code FUDA MOD 2 is now able to predict fuel performance parameter for burn-ups up to 50000 MWD/TeU. The validation field of the code has been extended to prediction of thorium oxide fuel performance. An analysis of local deformations at pellet interfaces and near the end caps is carried out considering the hourglassing of the pellet by finite element technique. (author). 15 refs, 1 fig.

Modification in the FUDA computer code to predict fuel performance at high burnup

International Nuclear Information System (INIS)

Das, M.; Arunakumar, B.V.; Prasad, P.N.

1997-01-01

The computer code FUDA (FUel Design Analysis) participated in the blind exercises organized by the IAEA CRP (Co-ordinated Research Programme) on FUMEX (Fuel Modelling at Extended Burnup). While the code prediction compared well with the experiments at Halden under various parametric and operating conditions, the fission gas release and fission gas pressure were found to be slightly over-predicted, particularly at high burnups. In view of the results of 6 FUMEX cases, the main models and submodels of the code were reviewed and necessary improvements were made. The new version of the code FUDA MOD 2 is now able to predict fuel performance parameter for burn-ups up to 50000 MWD/TeU. The validation field of the code has been extended to prediction of thorium oxide fuel performance. An analysis of local deformations at pellet interfaces and near the end caps is carried out considering the hourglassing of the pellet by finite element technique. (author). 15 refs, 1 fig

Designing Liquid Rocket Engine Injectors for Performance, Stability, and Cost

Science.gov (United States)

Westra, Douglas G.; West, Jeffrey S.

2014-01-01

NASA is developing the Space Launch System (SLS) for crewed exploration missions beyond low Earth orbit. Marshall Space Flight Center (MSFC) is designing rocket engines for the SLS Advanced Booster (AB) concepts being developed to replace the Shuttle-derived solid rocket boosters. One AB concept uses large, Rocket-Propellant (RP)-fueled engines that pose significant design challenges. The injectors for these engines require high performance and stable operation while still meeting aggressive cost reduction goals for access to space. Historically, combustion stability problems have been a critical issue for such injector designs. Traditional, empirical injector design tools and methodologies, however, lack the ability to reliably predict complex injector dynamics that often lead to combustion stability. Reliance on these tools alone would likely result in an unaffordable test-fail-fix cycle for injector development. Recently at MSFC, a massively parallel computational fluid dynamics (CFD) program was successfully applied in the SLS AB injector design process. High-fidelity reacting flow simulations were conducted for both single-element and seven-element representations of the full-scale injector. Data from the CFD simulations was then used to significantly augment and improve the empirical design tools, resulting in a high-performance, stable injector design.

Neural-Fuzzy Digital Strategy of Continuous-Time Nonlinear Systems Using Adaptive Prediction and Random-Local-Optimization Design

Directory of Open Access Journals (Sweden)

Zhi-Ren Tsai

2013-01-01

Full Text Available A tracking problem, time-delay, uncertainty and stability analysis of a predictive control system are considered. The predictive control design is based on the input and output of neural plant model (NPM, and a recursive fuzzy predictive tracker has scaling factors which limit the value zone of measured data and cause the tuned parameters to converge to obtain a robust control performance. To improve the further control performance, the proposed random-local-optimization design (RLO for a model/controller uses offline initialization to obtain a near global optimal model/controller. Other issues are the considerations of modeling error, input-delay, sampling distortion, cost, greater flexibility, and highly reliable digital products of the model-based controller for the continuous-time (CT nonlinear system. They are solved by a recommended two-stage control design with the first-stage (offline RLO and second-stage (online adaptive steps. A theorizing method is then put forward to replace the sensitivity calculation, which reduces the calculation of Jacobin matrices of the back-propagation (BP method. Finally, the feedforward input of reference signals helps the digital fuzzy controller improve the control performance, and the technique works to control the CT systems precisely.

Genomic Prediction of Barley Hybrid Performance

Directory of Open Access Journals (Sweden)

Norman Philipp

2016-07-01

Full Text Available Hybrid breeding in barley ( L. offers great opportunities to accelerate the rate of genetic improvement and to boost yield stability. A crucial requirement consists of the efficient selection of superior hybrid combinations. We used comprehensive phenotypic and genomic data from a commercial breeding program with the goal of examining the potential to predict the hybrid performances. The phenotypic data were comprised of replicated grain yield trials for 385 two-way and 408 three-way hybrids evaluated in up to 47 environments. The parental lines were genotyped using a 3k single nucleotide polymorphism (SNP array based on an Illumina Infinium assay. We implemented ridge regression best linear unbiased prediction modeling for additive and dominance effects and evaluated the prediction ability using five-fold cross validations. The prediction ability of hybrid performances based on general combining ability (GCA effects was moderate, amounting to 0.56 and 0.48 for two- and three-way hybrids, respectively. The potential of GCA-based hybrid prediction requires that both parental components have been evaluated in a hybrid background. This is not necessary for genomic prediction for which we also observed moderate cross-validated prediction abilities of 0.51 and 0.58 for two- and three-way hybrids, respectively. This exemplifies the potential of genomic prediction in hybrid barley. Interestingly, prediction ability using the two-way hybrids as training population and the three-way hybrids as test population or vice versa was low, presumably, because of the different genetic makeup of the parental source populations. Consequently, further research is needed to optimize genomic prediction approaches combining different source populations in barley.

Performance predictions affect attentional processes of event-based prospective memory.

Science.gov (United States)

Rummel, Jan; Kuhlmann, Beatrice G; Touron, Dayna R

2013-09-01

To investigate whether making performance predictions affects prospective memory (PM) processing, we asked one group of participants to predict their performance in a PM task embedded in an ongoing task and compared their performance with a control group that made no predictions. A third group gave not only PM predictions but also ongoing-task predictions. Exclusive PM predictions resulted in slower ongoing-task responding both in a nonfocal (Experiment 1) and in a focal (Experiment 2) PM task. Only in the nonfocal task was the additional slowing accompanied by improved PM performance. Even in the nonfocal task, however, was the correlation between ongoing-task speed and PM performance reduced after predictions, suggesting that the slowing was not completely functional for PM. Prediction-induced changes could be avoided by asking participants to additionally predict their performance in the ongoing task. In sum, the present findings substantiate a role of metamemory for attention-allocation strategies of PM. Copyright © 2013 Elsevier Inc. All rights reserved.

On line performance monitoring for predictive maintenance [Paper No.: VIA - 2

International Nuclear Information System (INIS)

Gupta, R.K.; Chandra, Rajesh

1981-01-01

There will always be progressive deterioration in the performance of dynamic equipment due to normal inevitable wear, malfunctions, failures and other reasons. In most cases it is possible to monitor some parameters of a system which would get progressively affected with the deterioration in the health of the system. By on-line monitoring of such predetermined parameters, compared with preset base data generated for a healthy system earlier, would prove very helpful in avoiding breakdowns and in proper planning of preventive and predictive maintenance. With increasing use of on-line computerised controls the generation of design base data and also the in-built self checking feature of monitoring the equipment health can be achieved by incorporating suitable software. This type of system will be helpful in: (a) predicting the life of component, (b) prewarning the operator about impending malfunctions, (c) establishing a maintenance schedule and spare inventory, and (d) analysing the failures. This type of centralised predictive maintenance is increasingly becoming important where: (a) the number of equipments are large, (b) the operation of equipment is critical from safety criteria, and (c) the minimum safety margin in the performance of the component is to be maintained. Keeping this in mind, the Fuel Handling System of Narora Atomic Power Project and the future power plants having computerised controls will have facility for on-line performance monitoring for predictive maintenance. The paper also describes methodology of the technique in detail, with a few representative cases. (author)

Multivariate performance reliability prediction in real-time

International Nuclear Information System (INIS)

Lu, S.; Lu, H.; Kolarik, W.J.

2001-01-01

This paper presents a technique for predicting system performance reliability in real-time considering multiple failure modes. The technique includes on-line multivariate monitoring and forecasting of selected performance measures and conditional performance reliability estimates. The performance measures across time are treated as a multivariate time series. A state-space approach is used to model the multivariate time series. Recursive forecasting is performed by adopting Kalman filtering. The predicted mean vectors and covariance matrix of performance measures are used for the assessment of system survival/reliability with respect to the conditional performance reliability. The technique and modeling protocol discussed in this paper provide a means to forecast and evaluate the performance of an individual system in a dynamic environment in real-time. The paper also presents an example to demonstrate the technique

Predicting Performance in Higher Education Using Proximal Predictors

Science.gov (United States)

Niessen, A. Susan M.; Meijer, Rob R.; Tendeiro, Jorge N.

2016-01-01

We studied the validity of two methods for predicting academic performance and student-program fit that were proximal to important study criteria. Applicants to an undergraduate psychology program participated in a selection procedure containing a trial-studying test based on a work sample approach, and specific skills tests in English and math. Test scores were used to predict academic achievement and progress after the first year, achievement in specific course types, enrollment, and dropout after the first year. All tests showed positive significant correlations with the criteria. The trial-studying test was consistently the best predictor in the admission procedure. We found no significant differences between the predictive validity of the trial-studying test and prior educational performance, and substantial shared explained variance between the two predictors. Only applicants with lower trial-studying scores were significantly less likely to enroll in the program. In conclusion, the trial-studying test yielded predictive validities similar to that of prior educational performance and possibly enabled self-selection. In admissions aimed at student-program fit, or in admissions in which past educational performance is difficult to use, a trial-studying test is a good instrument to predict academic performance. PMID:27073859

Could Learning Outcomes of the First Course in Accounting Predict Overall Academic Performance?

Science.gov (United States)

Alanzi, Khalid A.; Alfraih, Mishari M.

2017-01-01

Purpose: This study aims to question whether learning outcomes of the first course in accounting could predict the overall academic performance of accounting students as measured by their graduating grade point average (GPA). Design/methodology/approach The sample of the present study was drawn from accounting students who were graduated during…

Numerical analysis of the performance prediction for a thermoelectric generator

Energy Technology Data Exchange (ETDEWEB)

Kim, Chang Nyung [Kyung Hee University, Yongin (Korea, Republic of)

2015-09-15

The present study develops a two-dimensional numerical code that can predict the performance of a thermoelectric generator module including a p-leg/n-leg pair and top and bottom electrodes. The present code can simulate the detailed thermoelectric phenomena including the heat flow, electric current, Joule heating, Peltier heating, and Thomson heating, together with the efficiency of the modules whose properties depend on the temperature. The present numerical code can be used for the design optimization of a thermoelectric power generator.

Design and performance prediction of a new generation adsorption chiller using composite adsorbent

International Nuclear Information System (INIS)

Gong, L.X.; Wang, R.Z.; Xia, Z.Z.; Chen, C.J.

2011-01-01

Research highlights: → Composite adsorbent 'employing lithium chloride in silica gel' and water as working pair. → A new type adsorbent bed is used to accommodate the composite adsorbent. → A dynamic model of the adsorption chiller is built. → The coefficient of performance (COP) and the cooling capacity will be improved. -- Abstract: This paper presents a novel adsorption chiller using composite adsorbent 'employing lithium chloride in silica gel' as adsorbent and water as adsorbate. A new type adsorbent bed is used to accommodate the composite adsorbent. The mass recovery between two adsorbent beds usually results in the adsorbate unbalance. So a novel auto water makeup unite is used to solve the problem. A dynamic model of the adsorption chiller is built based on the adsorption isotherms to predict the performance. The simulation result shows that the coefficient of performance (COP) and the cooling capacity will increase by using this new composite adsorbent. When the temperatures of hot water inlet, cooling water inlet, and chilled water inlet are 363, 303 and 293 K, COP will be 0.43, and the cooling capacity will be 5.295 kW. Also operation strategy is optimized. Different temperatures of hot water inlet, cooling water inlet and chilling water inlet will result in different COP and cooling capacity.

Research on design methods and aerodynamics performance of CQUDTU-B21 airfoil

DEFF Research Database (Denmark)

Chen, Jin; Cheng, Jiangtao; Wen, Zhong Shen

2012-01-01

This paper presents the design methods of CQU-DTU-B21 airfoil for wind turbine. Compared with the traditional method of inverse design, the new method is described directly by a compound objective function to balance several conflicting requirements for design wind turbine airfoils, which based...... on design theory of airfoil profiles, blade element momentum (BEM) theory and airfoil Self-Noise prediction model. And then an optimization model with the target of maximum power performance on a 2D airfoil and low noise emission of design ranges for angle of attack has been developed for designing CQU......-DTU-B21 airfoil. To validate the optimization results, the comparison of the aerodynamics performance by XFOIL and wind tunnels test respectively at Re=3×106 is made between the CQU-DTU-B21 and DU93-W-210 which is widely used in wind turbines. © (2012) Trans Tech Publications, Switzerland....

The design and performance of seals for controlling radionuclide migration along boreholes, shafts and adits

International Nuclear Information System (INIS)

Broyd, T.W.

1993-01-01

Requirements for sealing an underground radioactive waste disposal facility are assessed, based on proposals for a deep repository in hard rock. Information is reviewed on the properties and performance characteristics of seals, of a range of materials, design and emplacement techniques, and for different industry end-uses. The ability to predict long-term seal performance is also addressed. Critical aspects of seal design and characteristics are proposed and recommendations are made for their performance testing. (author)

Optical simulations for design, alignment, and performance prediction of silicon pore optics for the ATHENA x-ray telescope

DEFF Research Database (Denmark)

Spiga, D.; Della Monica Ferreira, Desiree; Shortt, B.

2017-01-01

of these aspects is required in order to assess the fabrication and alignment tolerances; moreover, the achievable effective area and angular resolution depend on the mirror module design. Therefore, guaranteeing these optical performances requires: a fast design tool to find the most performing solution in terms...

Performative Urban Design

DEFF Research Database (Denmark)

Samson, Kristine

2011-01-01

visitors and participants to engage and interact with the city. Inspired by Lefebvre statement that "the most beautiful cities were those where festivals were not planned in advance” (Lefebvre 1987:36), I will discuss how urban designers can design engaging spaces, where the potentials of the city can...... unfold. Is it, for instance, the formal aesthetics of the design or rather the socio-cultural codes of the existing urban space that engage people? The paper engages in three urban performance designs: 1) The 10th Avenue Plaza at the Highline in New York 2) The temporary installations at Boble Plads......Urban design has come to mean many things. From the architectural masterplans to the informal urban design in temporary spaces and event designs. The paper will focus on urban designs engaging urban designs. Engaging urban design can broadly be understood as temporary design installations inviting...

Analog circuit design designing high performance amplifiers

CERN Document Server

Feucht, Dennis

2010-01-01

The third volume Designing High Performance Amplifiers applies the concepts from the first two volumes. It is an advanced treatment of amplifier design/analysis emphasizing both wideband and precision amplification.

Retrospective lifetime dietary patterns predict cognitive performance in community-dwelling older Australians.

Science.gov (United States)

Hosking, Diane E; Nettelbeck, Ted; Wilson, Carlene; Danthiir, Vanessa

2014-07-28

Dietary intake is a modifiable exposure that may have an impact on cognitive outcomes in older age. The long-term aetiology of cognitive decline and dementia, however, suggests that the relevance of dietary intake extends across the lifetime. In the present study, we tested whether retrospective dietary patterns from the life periods of childhood, early adulthood, adulthood and middle age predicted cognitive performance in a cognitively healthy sample of 352 older Australian adults >65 years. Participants completed the Lifetime Diet Questionnaire and a battery of cognitive tests designed to comprehensively assess multiple cognitive domains. In separate regression models, lifetime dietary patterns were the predictors of cognitive factor scores representing ten constructs derived by confirmatory factor analysis of the cognitive test battery. All regression models were progressively adjusted for the potential confounders of current diet, age, sex, years of education, English as native language, smoking history, income level, apoE ɛ4 status, physical activity, other past dietary patterns and health-related variables. In the adjusted models, lifetime dietary patterns predicted cognitive performance in this sample of older adults. In models additionally adjusted for intake from the other life periods and mechanistic health-related variables, dietary patterns from the childhood period alone reached significance. Higher consumption of the 'coffee and high-sugar, high-fat extras' pattern predicted poorer performance on simple/choice reaction time, working memory, retrieval fluency, short-term memory and reasoning. The 'vegetable and non-processed' pattern negatively predicted simple/choice reaction time, and the 'traditional Australian' pattern positively predicted perceptual speed and retrieval fluency. Identifying early-life dietary antecedents of older-age cognitive performance contributes to formulating strategies for delaying or preventing cognitive decline.

Predicting High-Power Performance in Professional Cyclists.

Science.gov (United States)

Sanders, Dajo; Heijboer, Mathieu; Akubat, Ibrahim; Meijer, Kenneth; Hesselink, Matthijs K

2017-03-01

To assess if short-duration (5 to ~300 s) high-power performance can accurately be predicted using the anaerobic power reserve (APR) model in professional cyclists. Data from 4 professional cyclists from a World Tour cycling team were used. Using the maximal aerobic power, sprint peak power output, and an exponential constant describing the decrement in power over time, a power-duration relationship was established for each participant. To test the predictive accuracy of the model, several all-out field trials of different durations were performed by each cyclist. The power output achieved during the all-out trials was compared with the predicted power output by the APR model. The power output predicted by the model showed very large to nearly perfect correlations to the actual power output obtained during the all-out trials for each cyclist (r = .88 ± .21, .92 ± .17, .95 ± .13, and .97 ± .09). Power output during the all-out trials remained within an average of 6.6% (53 W) of the predicted power output by the model. This preliminary pilot study presents 4 case studies on the applicability of the APR model in professional cyclists using a field-based approach. The decrement in all-out performance during high-intensity exercise seems to conform to a general relationship with a single exponential-decay model describing the decrement in power vs increasing duration. These results are in line with previous studies using the APR model to predict performance during brief all-out trials. Future research should evaluate the APR model with a larger sample size of elite cyclists.

Off-design performance analysis of organic Rankine cycle using real operation data from a heat source plant

International Nuclear Information System (INIS)

Kim, In Seop; Kim, Tong Seop; Lee, Jong Jun

2017-01-01

Highlights: • ORC systems driven by waste or residual heat from a combined cycle cogeneration plant were analyzed. • An off-design analysis model was developed and validated with commercial ORC data. • A procedure to predict the actual variation of ORC performance using the off-design model was set up. • The importance of using long-term operation data of the heat source plant was demonstrated. - Abstract: There has been increasing demand for cogeneration power plants, which provides high energy utilization. Research on upgrading power plant performance is also being actively pursued. The organic Rankine cycle (ORC) can operate with mid- and low-temperature heat sources and is suitable for enhancing performance of existing power plants. In this study, an off-design analysis model for the ORC was developed, which is driven by waste heat or residual heat from a combined cycle cogeneration plant. The applied heat sources are the exhaust gas from the heat recovery steam generator (Case 1) and waste heat from a heat storage unit (Case 2). Optimal design points of the ORC were selected based on the design heat source condition of each case. Then, the available ORC power output for each case was predicted using actual long-term plant operation data and a validated off-design analysis model. The ORC capacity of Case 2 was almost two times larger than that of Case 1. The predicted average electricity generation of both cases was less than the design output. The results of this paper reveal the importance of both the prediction of electricity generation using actual plant operation data and the need for optimal ORC system sizing.

Integrating geophysics and hydrology for reducing the uncertainty of groundwater model predictions and improved prediction performance

DEFF Research Database (Denmark)

Christensen, Nikolaj Kruse; Christensen, Steen; Ferre, Ty

the integration of geophysical data in the construction of a groundwater model increases the prediction performance. We suggest that modelers should perform a hydrogeophysical “test-bench” analysis of the likely value of geophysics data for improving groundwater model prediction performance before actually...... and the resulting predictions can be compared with predictions from the ‘true’ model. By performing this analysis we expect to give the modeler insight into how the uncertainty of model-based prediction can be reduced.......A major purpose of groundwater modeling is to help decision-makers in efforts to manage the natural environment. Increasingly, it is recognized that both the predictions of interest and their associated uncertainties should be quantified to support robust decision making. In particular, decision...

Micro-gas turbine performance optimization by off-design characteristics prediction. Paper no. IGEC-1-ID24

International Nuclear Information System (INIS)

Asgari, M.B.; Pahlevanzadeh, H.

2005-01-01

The design characteristics of a microturbine can be obtained according to geometrical features of major modules like compressor and turbine. Ambient temperature and pressure affect on micro-gas turbine performance. The customer requirements may be introduced some constraints on micro-gas turbine parameters. This work presents a program in Matlab to study the effect of surge margin on the behavior of the engine. It has been shown that the optimum performance could be obtained at 0.83-designed speed. Around the optimized speed, a marginal envelope was obtained. The results show that the fuel consumption 61% of design point, the power output 78% of design point and the efficiency 20.5%. It is easy to show that the principal results of simulation present an optimum region of operation rather than the one point for optimum conditions. Finally, a future work for studying the influence of heat exchanger on efficiency and development of a model of the power electronics so that the complete system can be simulated from power generation is suggested. (author)

Predicting Expressive Dynamics in Piano Performances using Neural Networks

NARCIS (Netherlands)

van Herwaarden, Sam; Grachten, Maarten; de Haas, W. Bas

2014-01-01

This paper presents a model for predicting expressive accentuation in piano performances with neural networks. Using Restricted Boltzmann Machines (RBMs), features are learned from performance data, after which these features are used to predict performed loudness. During feature learning, data

Gate valve performance prediction

International Nuclear Information System (INIS)

Harrison, D.H.; Damerell, P.S.; Wang, J.K.; Kalsi, M.S.; Wolfe, K.J.

1994-01-01

The Electric Power Research Institute is carrying out a program to improve the performance prediction methods for motor-operated valves. As part of this program, an analytical method to predict the stem thrust required to stroke a gate valve has been developed and has been assessed against data from gate valve tests. The method accounts for the loads applied to the disc by fluid flow and for the detailed mechanical interaction of the stem, disc, guides, and seats. To support development of the method, two separate-effects test programs were carried out. One test program determined friction coefficients for contacts between gate valve parts by using material specimens in controlled environments. The other test program investigated the interaction of the stem, disc, guides, and seat using a special fixture with full-sized gate valve parts. The method has been assessed against flow-loop and in-plant test data. These tests include valve sizes from 3 to 18 in. and cover a considerable range of flow, temperature, and differential pressure. Stem thrust predictions for the method bound measured results. In some cases, the bounding predictions are substantially higher than the stem loads required for valve operation, as a result of the bounding nature of the friction coefficients in the method

Numerical and experimental investigation on the performance of three newly designed 100 kW-class tidal current turbines

Directory of Open Access Journals (Sweden)

Museok Song

2012-09-01

Full Text Available Three types of 100 kW-class tidal stream turbines are proposed and their performance is studied both numerically and experimentally. Following a wind turbine design procedure, a base blade is derived and two additional blades are newly designed focusing more on efficiency and cavitation. For the three designed turbines, a CFD is performed by using FLUENT. The calculations predict that the newly designed turbines perform better than the base turbine and the tip vortex can be reduced with additional efficiency increase by adopting a tip rake. The performance of the turbines is tested in a towing tank with 700 mm models. The scale problem is carefully investigated and the measurements are compared with the CFD results. All the prediction from the CFD is supported by the model experiment with some quantitative discrepancy. The maximum efficiencies are 0.49 (CFD and 0.45 (experiment at TSR 5.17 for the turbine with a tip rake.

Performative Computation-aided Design Optimization

Directory of Open Access Journals (Sweden)

Ming Tang

2012-12-01

Full Text Available This article discusses a collaborative research and teaching project between the University of Cincinnati, Perkins+Will’s Tech Lab, and the University of North Carolina Greensboro. The primary investigation focuses on the simulation, optimization, and generation of architectural designs using performance-based computational design approaches. The projects examine various design methods, including relationships between building form, performance and the use of proprietary software tools for parametric design.

Comparison of nuclear safety research reactor (TRIGA-ACPR) performance with analytical prediction

International Nuclear Information System (INIS)

West, G.B.; Whittemore, W.L.

1976-01-01

The NSRR was taken critical on June 30, 1975 at the Japan Atomic Energy Research Institute - Tokai-mura, Japan. Following initial core loading and control rod calibration, a series of pulsing tests was performed to characterize the performance of the reactor. A comparison has been made of performance parameters actually measured in the 157 element core versus predicted values based upon design analyses. The nuclear parameters measured were quite close to prediction. A $4.70 pulse produced a minimum period of 1.12 msec, a peak power of 20,500 MW and yielded a prompt energy release of 103 MW-sec. Pulse tests with experimental UO 2 fuel pins in the central irradiation cavity have produced 320 cal/gm, averaged at the axial center of 10% enriched UO 2 , for a 100 MW-sec pulse. The pulse rods for the NSRR contain B 4 C enriched to about 93 percent in Boron-10 in order to achieve maximum design performance with only three pulse rods. The total worth for the three transient rods was measured to be about $5.05 (vs $5.07 calculated for the 165 element core), thus verifying the effectiveness of the Boron-10 enrichment to achieve the desired result. Analysis of fuel temperature measurements made in the NSRR show that, for fuel temperatures produced during pulsing greater than 900 deg. C, heat transfer in the 0.010-inch gap between fuel and clad is enhanced by the minor outgassing of hydrogen which is characteristic of that temperature region. The hydrogen is normally all reabsorbed within about 100 sec of maximum temperature, at which time the heat transfer is characteristic of air (or argon) in the gap. In some of the temperature-instrumented elements, however, all of the hydrogen was not reabsorbed and as a result these elements gave significantly lower temperatures for high power steady state operation than were recorded prior to pulsing. In general, the NSRR parameters measured during startup were quite close to analytical prediction and the overall performance of the

High-Performance Cryogenic Designs for OMEGA and the National Ignition Facility

Science.gov (United States)

Goncharov, V. N.; Collins, T. J. B.; Marozas, J. A.; Regan, S. P.; Betti, R.; Boehly, T. R.; Campbell, E. M.; Froula, D. H.; Igumenshchev, I. V.; McCrory, R. L.; Myatt, J. F.; Radha, P. B.; Sangster, T. C.; Shvydky, A.

2016-10-01

The main advantage of laser symmetric direct drive (SDD) is a significantly higher coupled drive laser energy to the hot-spot internal energy at stagnation compared to that of laser indirect drive. Because of coupling losses resulting from cross-beam energy transfer (CBET), however, reaching ignition conditions on the NIF with SDD requires designs with excessively large in-flight aspect ratios ( 30). Results of cryogenic implosions performed on OMEGA show that such designs are unstable to short-scale nonuniformity growth during shell implosion. Several CBET reduction strategies have been proposed in the past. This talk will discuss high-performing designs using several CBET-mitigation techniques, including using drive laser beams smaller than the target size and wavelength detuning. Designs that are predicted to reach alpha burning regimes as well as a gain of 10 to 40 at the NIF-scale will be presented. Hydrodynamically scaled OMEGA designs with similar CBET-reduction techniques will also be discussed. This material is based upon work supported by the Department Of Energy National Nuclear Security Administration under Award Number DE-NA0001944.

Neuropsychological test performance and prediction of functional capacities among Spanish-speaking and English-speaking patients with dementia.

Science.gov (United States)

Loewenstein, D A; Rubert, M P; Argüelles, T; Duara, R

1995-03-01

Neuropsychological measures have been widely used by clinicians to assist them in making judgments regarding a cognitively impaired patient's ability to independently perform important activities of daily living. However, important questions have been raised concerning the degree to which neuropsychological instruments can predict a broad array of specific functional capacities required in the home environment. In the present study, we examined 127 English-speaking and 56 Spanish-speaking patients with Alzheimer's disease (AD) and determined the extent to which various neuropsychological measures and demographic variables were predictive of performance on functional measures administered within the clinical setting. Among English-speaking AD patients, Block Design and Digit-Span of the WAIS-R, as well as tests of language were among the strongest predictors of functional performance. For Spanish-speakers, Block Design, The Mini-Mental State Evaluation (MMSE) and Digit Span had the optimal predictive power. When stepwise regression was conducted on the entire sample of 183 subjects, ethnicity emerged as a statistically significant predictor variable on one of the seven functional tests (writing a check). Despite the predictive power of several of the neuropsychological measures for both groups, most of the variability in objective functional performance could not be explained in our regression models. As a result, it would appear prudent to include functional measures as part of a comprehensive neuropsychological evaluation for dementia.

Reliable predictions of waste performance in a geologic repository

International Nuclear Information System (INIS)

Pigford, T.H.; Chambre, P.L.

1985-08-01

Establishing reliable estimates of long-term performance of a waste repository requires emphasis upon valid theories to predict performance. Predicting rates that radionuclides are released from waste packages cannot rest upon empirical extrapolations of laboratory leach data. Reliable predictions can be based on simple bounding theoretical models, such as solubility-limited bulk-flow, if the assumed parameters are reliably known or defensibly conservative. Wherever possible, performance analysis should proceed beyond simple bounding calculations to obtain more realistic - and usually more favorable - estimates of expected performance. Desire for greater realism must be balanced against increasing uncertainties in prediction and loss of reliability. Theoretical predictions of release rate based on mass-transfer analysis are bounding and the theory can be verified. Postulated repository analogues to simulate laboratory leach experiments introduce arbitrary and fictitious repository parameters and are shown not to agree with well-established theory. 34 refs., 3 figs., 2 tabs

Predictive validity of pre-admission assessments on medical student performance.

Science.gov (United States)

Dabaliz, Al-Awwab; Kaadan, Samy; Dabbagh, M Marwan; Barakat, Abdulaziz; Shareef, Mohammad Abrar; Al-Tannir, Mohamad; Obeidat, Akef; Mohamed, Ayman

2017-11-24

To examine the predictive validity of pre-admission variables on students' performance in a medical school in Saudi Arabia. In this retrospective study, we collected admission and college performance data for 737 students in preclinical and clinical years. Data included high school scores and other standardized test scores, such as those of the National Achievement Test and the General Aptitude Test. Additionally, we included the scores of the Test of English as a Foreign Language (TOEFL) and the International English Language Testing System (IELTS) exams. Those datasets were then compared with college performance indicators, namely the cumulative Grade Point Average (cGPA) and progress test, using multivariate linear regression analysis. In preclinical years, both the National Achievement Test (p=0.04, B=0.08) and TOEFL (p=0.017, B=0.01) scores were positive predictors of cGPA, whereas the General Aptitude Test (p=0.048, B=-0.05) negatively predicted cGPA. Moreover, none of the pre-admission variables were predictive of progress test performance in the same group. On the other hand, none of the pre-admission variables were predictive of cGPA in clinical years. Overall, cGPA strongly predict-ed students' progress test performance (p<0.001 and B=19.02). Only the National Achievement Test and TOEFL significantly predicted performance in preclinical years. However, these variables do not predict progress test performance, meaning that they do not predict the functional knowledge reflected in the progress test. We report various strengths and deficiencies in the current medical college admission criteria, and call for employing more sensitive and valid ones that predict student performance and functional knowledge, especially in the clinical years.

Predictive performance models and multiple task performance

Science.gov (United States)

Wickens, Christopher D.; Larish, Inge; Contorer, Aaron

1989-01-01

Five models that predict how performance of multiple tasks will interact in complex task scenarios are discussed. The models are shown in terms of the assumptions they make about human operator divided attention. The different assumptions about attention are then empirically validated in a multitask helicopter flight simulation. It is concluded from this simulation that the most important assumption relates to the coding of demand level of different component tasks.

Determination of a suitable set of loss models for centrifugal compressor performance prediction

Directory of Open Access Journals (Sweden)

Elkin I. GUTIÉRREZ VELÁSQUEZ

2017-10-01

Full Text Available Performance prediction in preliminary design stages of several turbomachinery components is a critical task in order to bring the design processes of these devices to a successful conclusion. In this paper, a review and analysis of the major loss mechanisms and loss models, used to determine the efficiency of a single stage centrifugal compressor, and a subsequent examination to determine an appropriate loss correlation set for estimating the isentropic efficiency in preliminary design stages of centrifugal compressors, were developed. Several semi-empirical correlations, commonly used to predict the efficiency of centrifugal compressors, were implemented in FORTRAN code and then were compared with experimental results in order to establish a loss correlation set to determine, with good approximation, the isentropic efficiency of single stage compressor. The aim of this study is to provide a suitable loss correlation set for determining the isentropic efficiency of a single stage centrifugal compressor, because, with a large amount of loss mechanisms and correlations available in the literature, it is difficult to ascertain how many and which correlations to employ for the correct prediction of the efficiency in the preliminary stage design of a centrifugal compressor. As a result of this study, a set of correlations composed by nine loss mechanisms for single stage centrifugal compressors, conformed by a rotor and a diffuser, are specified.

Simulation and prediction for energy dissipaters and stilling basins design using artificial intelligence technique

Directory of Open Access Journals (Sweden)

Mostafa Ahmed Moawad Abdeen

2015-12-01

Full Text Available Water with large velocities can cause considerable damage to channels whose beds are composed of natural earth materials. Several stilling basins and energy dissipating devices have been designed in conjunction with spillways and outlet works to avoid damages in canals’ structures. In addition, lots of experimental and traditional mathematical numerical works have been performed to profoundly investigate the accurate design of these stilling basins and energy dissipaters. The current study is aimed toward introducing the artificial intelligence technique as new modeling tool in the prediction of the accurate design of stilling basins. Specifically, artificial neural networks (ANNs are utilized in the current study in conjunction with experimental data to predict the length of the hydraulic jumps occurred in spillways and consequently the stilling basin dimensions can be designed for adequate energy dissipation. The current study showed, in a detailed fashion, the development process of different ANN models to accurately predict the hydraulic jump lengths acquired from different experimental studies. The results obtained from implementing these models showed that ANN technique was very successful in simulating the hydraulic jump characteristics occurred in stilling basins. Therefore, it can be safely utilized in the design of these basins as ANN involves minimum computational and financial efforts and requirements compared with experimental work and traditional numerical techniques such as finite difference or finite elements.

A prediction of 3-D viscous flow and performance of the NASA Low-Speed Centrifugal Compressor

Science.gov (United States)

Moore, John; Moore, Joan G.

1990-01-01

A prediction of the three-dimensional turbulent flow in the NASA Low-Speed Centrifugal Compressor Impeller has been made. The calculation was made for the compressor design conditions with the specified uniform tip clearance gap. The predicted performance is significantly worse than that predicted in the NASA design study. This is explained by the high tip leakage flow in the present calculation and by the different model adopted for tip leakage flow mixing. The calculation gives an accumulation of high losses in the shroud/pressure-side quadrant near the exit of the impeller. It also predicts a region of meridional backflow near the shroud wall. Both of these flow features should be extensive enough in the NASA impeller to allow detailed flow measurements, leading to improved flow modeling. Recommendations are made for future flow studies in the NASA impeller.

Geographic and temporal validity of prediction models: Different approaches were useful to examine model performance

NARCIS (Netherlands)

P.C. Austin (Peter); D. van Klaveren (David); Y. Vergouwe (Yvonne); D. Nieboer (Daan); D.S. Lee (Douglas); E.W. Steyerberg (Ewout)

2016-01-01

textabstractObjective: Validation of clinical prediction models traditionally refers to the assessment of model performance in new patients. We studied different approaches to geographic and temporal validation in the setting of multicenter data from two time periods. Study Design and Setting: We

Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

Science.gov (United States)

Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.

2014-01-01

This paper presents recent thermal model results of the Advanced Stirling Radioisotope Generator (ASRG). The three-dimensional (3D) ASRG thermal power model was built using the Thermal Desktop(trademark) thermal analyzer. The model was correlated with ASRG engineering unit test data and ASRG flight unit predictions from Lockheed Martin's (LM's) I-deas(trademark) TMG thermal model. The auxiliary cooling system (ACS) of the ASRG is also included in the ASRG thermal model. The ACS is designed to remove waste heat from the ASRG so that it can be used to heat spacecraft components. The performance of the ACS is reported under nominal conditions and during a Venus flyby scenario. The results for the nominal case are validated with data from Lockheed Martin. Transient thermal analysis results of ASRG for a Venus flyby with a representative trajectory are also presented. In addition, model results of an ASRG mounted on a Cassini-like spacecraft with a sunshade are presented to show a way to mitigate the high temperatures of a Venus flyby. It was predicted that the sunshade can lower the temperature of the ASRG alternator by 20 C for the representative Venus flyby trajectory. The 3D model also was modified to predict generator performance after a single Advanced Stirling Convertor failure. The geometry of the Microtherm HT insulation block on the outboard side was modified to match deformation and shrinkage observed during testing of a prototypic ASRG test fixture by LM. Test conditions and test data were used to correlate the model by adjusting the thermal conductivity of the deformed insulation to match the post-heat-dump steady state temperatures. Results for these conditions showed that the performance of the still-functioning inboard ACS was unaffected.

Virtual Design Studio (VDS) - Development of an Integrated Computer Simulation Environment for Performance Based Design of Very-Low Energy and High IEQ Buildings

Energy Technology Data Exchange (ETDEWEB)

Chen, Yixing [Building Energy and Environmental Systems Lab. (BEESL), Syracuse, NY (United States); Zhang, Jianshun [Syracuse Univ., NY (United States); Pelken, Michael [Syracuse Univ., NY (United States); Gu, Lixing [Univ. of Central Florida, Orlando, FL (United States); Rice, Danial [Building Energy and Environmental Systems Lab. (BEESL), Syracuse, NY (United States); Meng, Zhaozhou [Building Energy and Environmental Systems Lab. (BEESL), Syracuse, NY (United States); Semahegn, Shewangizaw [Building Energy and Environmental Systems Lab. (BEESL), Syracuse, NY (United States); Feng, Wei [Building Energy and Environmental Systems Lab. (BEESL), Syracuse, NY (United States); Ling, Francesca [Syracuse Univ., NY (United States); Shi, Jun [Building Energy and Environmental Systems Lab. (BEESL), Syracuse, NY (United States); Henderson, Hugh [CDH Energy, Cazenovia, NY (United States)

2013-09-01

on evaluating thermal performance, air quality and lighting environmental quality because of their strong interaction with the energy performance of buildings. The VDS software framework contains four major functions: 1) Design coordination: It enables users to define tasks using the Input-Process-Output flow approach, which specifies the anticipated activities (i.e., the process), required input and output information, and anticipated interactions with other tasks. It also allows task scheduling to define the work flow, and sharing of the design data and information via the internet. 2) Modeling and simulation: It enables users to perform building simulations to predict the energy consumption and IEQ conditions at any of the design stages by using EnergyPlus and a combined heat, air, moisture and pollutant simulation (CHAMPS) model. A method for co-simulation was developed to allow the use of both models at the same time step for the combined energy and indoor air quality analysis. 3) Results visualization: It enables users to display a 3-D geometric design of the building by reading BIM (building information model) file generated by design software such as SketchUp, and the predicted results of heat, air, moisture, pollutant and light distributions in the building. 4) Performance evaluation: It enables the users to compare the performance of a proposed building design against a reference building that is defined for the same type of buildings under the same climate condition, and predicts the percent of improvements over the minimum requirements specified in ASHRAE Standard 55-2010, 62.1-2010 and 90.1-2010. An approach was developed to estimate the potential impact of a design factor on the whole building performance, and hence can assist the user to identify areas that have most pay back for investment. The VDS software was developed by using C++ with the conventional Model, View and Control (MVC) software architecture. The software has been verified by using a

Attention in aviation. [to aircraft design and pilot performance

Science.gov (United States)

Wickens, Christopher D.

1987-01-01

The relevance of four principles or mechanisms of human attention to the design of aviation systems and the performance of pilots in multitask environments, including workload prediction and measurement, control-display integration, and the use of voice and head-up displays is discussed. The principles are: the mental energy that supplies task performance (resources), the resulting cross-talk between tasks as they are made more similar (confusion), the combination of different task elements (integration), and the way in which one task is processed and another is ignored (selection or tunneling). The introduction of greater levels of complexity into the validation of attentional theories in order to approach the demands of the cockpit or ATC console is proposed.

Performance prediction method for a multi-stage Knudsen pump

Science.gov (United States)

Kugimoto, K.; Hirota, Y.; Kizaki, Y.; Yamaguchi, H.; Niimi, T.

2017-12-01

In this study, the novel method to predict the performance of a multi-stage Knudsen pump is proposed. The performance prediction method is carried out in two steps numerically with the assistance of a simple experimental result. In the first step, the performance of a single-stage Knudsen pump was measured experimentally under various pressure conditions, and the relationship of the mass flow rate was obtained with respect to the average pressure between the inlet and outlet of the pump and the pressure difference between them. In the second step, the performance of a multi-stage pump was analyzed by a one-dimensional model derived from the mass conservation law. The performances predicted by the 1D-model of 1-stage, 2-stage, 3-stage, and 4-stage pumps were validated by the experimental results for the corresponding number of stages. It was concluded that the proposed prediction method works properly.

Design and Output Performance Model of Turbodrill Blade Used in a Slim Borehole

Directory of Open Access Journals (Sweden)

Yu Wang

2016-12-01

Full Text Available Small-diameter turbodrills have great potential for use in slim boreholes because of their lower cost and higher efficiency when used in geothermal energy and other underground resource applications. Multistage hydraulic components consisting of stators and rotors are key aspects of turbodrills. This study aimed to develop a suitable blade that can be used under high temperature in granite formations. First, prediction models for single- and multi-stage blades were established based on Bernoulli’s Equation. The design requirement of the blade for high-temperature geothermal drilling in granite was proposed. A Φ89 blade was developed based on the dimensionless parameter method and Bezier curve; the parameters of the blade, including its radial size, symotric parameters, and blade profiles, were input into ANASYS and CFX to establish a calculation model of the single-stage blade. The optimization of the blade structure of the small-diameter turbodrill enabled a multistage turbodrill model to be established and the turbodrill’s overall output performance to be predicted. The results demonstrate that the design can meet the turbodrill’s performance requirements and that the multistage model can effectively improve the accuracy of the prediction.

Improved Helicopter Rotor Performance Prediction through Loose and Tight CFD/CSD Coupling

Science.gov (United States)

Ickes, Jacob C.

Helicopters and other Vertical Take-Off or Landing (VTOL) vehicles exhibit an interesting combination of structural dynamic and aerodynamic phenomena which together drive the rotor performance. The combination of factors involved make simulating the rotor a challenging and multidisciplinary effort, and one which is still an active area of interest in the industry because of the money and time it could save during design. Modern tools allow the prediction of rotorcraft physics from first principles. Analysis of the rotor system with this level of accuracy provides the understanding necessary to improve its performance. There has historically been a divide between the comprehensive codes which perform aeroelastic rotor simulations using simplified aerodynamic models, and the very computationally intensive Navier-Stokes Computational Fluid Dynamics (CFD) solvers. As computer resources become more available, efforts have been made to replace the simplified aerodynamics of the comprehensive codes with the more accurate results from a CFD code. The objective of this work is to perform aeroelastic rotorcraft analysis using first-principles simulations for both fluids and structural predictions using tools available at the University of Toledo. Two separate codes are coupled together in both loose coupling (data exchange on a periodic interval) and tight coupling (data exchange each time step) schemes. To allow the coupling to be carried out in a reliable and efficient way, a Fluid-Structure Interaction code was developed which automatically performs primary functions of loose and tight coupling procedures. Flow phenomena such as transonics, dynamic stall, locally reversed flow on a blade, and Blade-Vortex Interaction (BVI) were simulated in this work. Results of the analysis show aerodynamic load improvement due to the inclusion of the CFD-based airloads in the structural dynamics analysis of the Computational Structural Dynamics (CSD) code. Improvements came in the form

Calibration of PMIS pavement performance prediction models.

Science.gov (United States)

2012-02-01

Improve the accuracy of TxDOTs existing pavement performance prediction models through calibrating these models using actual field data obtained from the Pavement Management Information System (PMIS). : Ensure logical performance superiority patte...

Design of Probabilistic Random Forests with Applications to Anticancer Drug Sensitivity Prediction.

Science.gov (United States)

Rahman, Raziur; Haider, Saad; Ghosh, Souparno; Pal, Ranadip

2015-01-01

Random forests consisting of an ensemble of regression trees with equal weights are frequently used for design of predictive models. In this article, we consider an extension of the methodology by representing the regression trees in the form of probabilistic trees and analyzing the nature of heteroscedasticity. The probabilistic tree representation allows for analytical computation of confidence intervals (CIs), and the tree weight optimization is expected to provide stricter CIs with comparable performance in mean error. We approached the ensemble of probabilistic trees' prediction from the perspectives of a mixture distribution and as a weighted sum of correlated random variables. We applied our methodology to the drug sensitivity prediction problem on synthetic and cancer cell line encyclopedia dataset and illustrated that tree weights can be selected to reduce the average length of the CI without increase in mean error.

Energy Prediction versus Energy Performance of Green Buildings in Malaysia. Comparison of Predicted and Operational Measurement of GBI Certified Green Office in Kuala Lumpur

Directory of Open Access Journals (Sweden)

Zaid Suzaini M

2016-01-01

Full Text Available Forward from the sustainability agenda of Brundtland in 1987 and the increasing demand for energy efficient buildings, the building industry has taken steps in meeting the challenge of reducing its environmental impact. Initiatives such as ‘green’ or ‘sustainable’ design have been at the forefront of architecture, while green assessment tools have been used to predict the energy performance of building during its operational phase. However, there is still a significant hap between predicted or simulated energy measurements compared to actual operational energy consumption, or is more commonly referred as the ‘performance gap’. This paper tries to bridge this gap by comparing measured operational energy consumption of a Green Building Index (GBI certified office building in Kuala Lumpur, with its predicted energy rating qualification.

Prediction of multi performance characteristics of wire EDM process using grey ANFIS

Science.gov (United States)

Kumanan, Somasundaram; Nair, Anish

2017-09-01

Super alloys are used to fabricate components in ultra-supercritical power plants. These hard to machine materials are processed using non-traditional machining methods like Wire cut electrical discharge machining and needs attention. This paper details about multi performance optimization of wire EDM process using Grey ANFIS. Experiments are designed to establish the performance characteristics of wire EDM such as surface roughness, material removal rate, wire wear rate and geometric tolerances. The control parameters are pulse on time, pulse off time, current, voltage, flushing pressure, wire tension, table feed and wire speed. Grey relational analysis is employed to optimise the multi objectives. Analysis of variance of the grey grades is used to identify the critical parameters. A regression model is developed and used to generate datasets for the training of proposed adaptive neuro fuzzy inference system. The developed prediction model is tested for its prediction ability.

Integrated Detection and Prediction of Influenza Activity for Real-Time Surveillance: Algorithm Design.

Science.gov (United States)

Spreco, Armin; Eriksson, Olle; Dahlström, Örjan; Cowling, Benjamin John; Timpka, Toomas

2017-06-15

Influenza is a viral respiratory disease capable of causing epidemics that represent a threat to communities worldwide. The rapidly growing availability of electronic "big data" from diagnostic and prediagnostic sources in health care and public health settings permits advance of a new generation of methods for local detection and prediction of winter influenza seasons and influenza pandemics. The aim of this study was to present a method for integrated detection and prediction of influenza virus activity in local settings using electronically available surveillance data and to evaluate its performance by retrospective application on authentic data from a Swedish county. An integrated detection and prediction method was formally defined based on a design rationale for influenza detection and prediction methods adapted for local surveillance. The novel method was retrospectively applied on data from the winter influenza season 2008-09 in a Swedish county (population 445,000). Outcome data represented individuals who met a clinical case definition for influenza (based on International Classification of Diseases version 10 [ICD-10] codes) from an electronic health data repository. Information from calls to a telenursing service in the county was used as syndromic data source. The novel integrated detection and prediction method is based on nonmechanistic statistical models and is designed for integration in local health information systems. The method is divided into separate modules for detection and prediction of local influenza virus activity. The function of the detection module is to alert for an upcoming period of increased load of influenza cases on local health care (using influenza-diagnosis data), whereas the function of the prediction module is to predict the timing of the activity peak (using syndromic data) and its intensity (using influenza-diagnosis data). For detection modeling, exponential regression was used based on the assumption that the beginning

Predictability by recognizable road design. [previously called: Recognizable road design.

NARCIS (Netherlands)

2007-01-01

One of the Sustainable Safety principles is that a road should have a recognizable design and a predictable alignment. If this is the case, road users know how they are expected to behave and what they can expect from other road users, so that crashes may be prevented. For roads to be recognizable,

An assessment of the validity of inelastic design analysis methods by comparisons of predictions with test results

International Nuclear Information System (INIS)

Corum, J.M.; Clinard, J.A.; Sartory, W.K.

1976-01-01

The use of computer programs that employ relatively complex constitutive theories and analysis procedures to perform inelastic design calculations on fast reactor system components introduces questions of validation and acceptance of the analysis results. We may ask ourselves, ''How valid are the answers.'' These questions, in turn, involve the concepts of verification of computer programs as well as qualification of the computer programs and of the underlying constitutive theories and analysis procedures. This paper addresses the latter - the qualification of the analysis methods for inelastic design calculations. Some of the work underway in the United States to provide the necessary information to evaluate inelastic analysis methods and computer programs is described, and typical comparisons of analysis predictions with inelastic structural test results are presented. It is emphasized throughout that rather than asking ourselves how valid, or correct, are the analytical predictions, we might more properly question whether or not the combination of the predictions and the associated high-temperature design criteria leads to an acceptable level of structural integrity. It is believed that in this context the analysis predictions are generally valid, even though exact correlations between predictions and actual behavior are not obtained and cannot be expected. Final judgment, however, must be reserved for the design analyst in each specific case. (author)

Predicting Performance Ratings Using Motivational Antecedents

National Research Council Canada - National Science Library

Zazania, Michelle

1998-01-01

This research examined the role of motivation in predicting peer and trainer ratings of student performance and contrasted the relative importance of various antecedents for peer and trainer ratings...

Model predictive controller design of hydrocracker reactors

OpenAIRE

GÖKÇE, Dila

2011-01-01

This study summarizes the design of a Model Predictive Controller (MPC) in Tüpraş, İzmit Refinery Hydrocracker Unit Reactors. Hydrocracking process, in which heavy vacuum gasoil is converted into lighter and valuable products at high temperature and pressure is described briefly. Controller design description, identification and modeling studies are examined and the model variables are presented. WABT (Weighted Average Bed Temperature) equalization and conversion increase are simulate...

Statistical and Machine Learning Models to Predict Programming Performance

OpenAIRE

Bergin, Susan

2006-01-01

This thesis details a longitudinal study on factors that influence introductory programming success and on the development of machine learning models to predict incoming student performance. Although numerous studies have developed models to predict programming success, the models struggled to achieve high accuracy in predicting the likely performance of incoming students. Our approach overcomes this by providing a machine learning technique, using a set of three significant...

Control System Design for Cylindrical Tank Process Using Neural Model Predictive Control Technique

Directory of Open Access Journals (Sweden)

M. Sridevi

2010-10-01

Full Text Available Chemical manufacturing and process industry requires innovative technologies for process identification. This paper deals with model identification and control of cylindrical process. Model identification of the process was done using ARMAX technique. A neural model predictive controller was designed for the identified model. The performance of the controllers was evaluated using MATLAB software. The performance of NMPC controller was compared with Smith Predictor controller and IMC controller based on rise time, settling time, overshoot and ISE and it was found that the NMPC controller is better suited for this process.

A formalized design process for bacterial consortia that perform logic computing.

Directory of Open Access Journals (Sweden)

Weiyue Ji

Full Text Available The concept of microbial consortia is of great attractiveness in synthetic biology. Despite of all its benefits, however, there are still problems remaining for large-scaled multicellular gene circuits, for example, how to reliably design and distribute the circuits in microbial consortia with limited number of well-behaved genetic modules and wiring quorum-sensing molecules. To manage such problem, here we propose a formalized design process: (i determine the basic logic units (AND, OR and NOT gates based on mathematical and biological considerations; (ii establish rules to search and distribute simplest logic design; (iii assemble assigned basic logic units in each logic operating cell; and (iv fine-tune the circuiting interface between logic operators. We in silico analyzed gene circuits with inputs ranging from two to four, comparing our method with the pre-existing ones. Results showed that this formalized design process is more feasible concerning numbers of cells required. Furthermore, as a proof of principle, an Escherichia coli consortium that performs XOR function, a typical complex computing operation, was designed. The construction and characterization of logic operators is independent of "wiring" and provides predictive information for fine-tuning. This formalized design process provides guidance for the design of microbial consortia that perform distributed biological computation.

Predictive analytics tools to adjust and monitor performance metrics for the ATLAS Production System

CERN Document Server

Barreiro Megino, Fernando Harald; The ATLAS collaboration

2017-01-01

Having information such as an estimation of the processing time or possibility of system outage (abnormal behaviour) helps to assist to monitor system performance and to predict its next state. The current cyber-infrastructure presents computing conditions in which contention for resources among high-priority data analysis happens routinely, that might lead to significant workload and data handling interruptions. The lack of the possibility to monitor and to predict the behaviour of the analysis process (its duration) and system’s state itself caused to focus on design of the built-in situational awareness analytic tools.

[Design of a preoperative predictive score for choledocholithiasis].

Science.gov (United States)

Bueno Lledó, Jose; Ibáñez Cirión, Jose Luis; Torregrosa Gallud, Antonio; López Andújar, Rafael

2014-11-01

Choledocholithiasis is the most common cause of obstructive jaundice and occurs in 5-10% of patients with cholelithiasis. To design a preoperative predictive score for choledocholithiasis. A prospective study was carried out in 556 patients admitted to our department for biliary disease. Preoperative clinical, laboratory, and ultrasound variables were compared between patients without choledocholithiasis and 65 patients with this diagnosis. A multivariate logistic analysis was performed to obtain a predictive model of choledocholithiasis, determining sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Predictors of choledocholithiasis were the presence of a prior history of biliary disease (history of biliary colic, acute cholecystitis, choledocholithiasis or acute biliary pancreatitis) (p=0.021, OR=2.225, 95% CI: 1.130-4.381), total bilirubin values >4mg/dl (p=0.046, OR=2.403, 95% CI: 1.106-5.685), alkaline phosphatase values >150mg/dl (p=0.022 income, OR=2.631, 95%: 1.386-6.231), gamma-glutamyltransferase (GGT) values >100mg/dl (p=0.035, OR=2.10, 95% CI: 1.345-5.850), and an ultrasound finding of biliary duct >8mm (p=0.034, OR=3.063 95% CI: 1086-8649). A score superior to 5 had a specificity and PPV of 100% for detecting choledocholithiasis and a score less than 3 had a sensitivity and NPV of 100% for excluding this diagnosis. The preoperative score can exclude or confirm the presence of choledocholithiasis and allows patients to directly benefit from laparoscopic cholecystectomy (LC) or prior endoscopic retrograde cholangiopancreatography (ERCP). Copyright © 2014 Elsevier España, S.L.U. and AEEH y AEG. All rights reserved.

Prediction of Job Performance: Review of Military Studies

Science.gov (United States)

1982-03-01

an assessment center to predict filed leadership performance of Army officers and NCOs. Proceedings of the 19th Annual Military Testing Association...C. Behaviors, results, and organizational effectiveness: The problem of criteria. In Dunnette, M. D. (Ed.), Handbook of Industrial and organizatin ...than for the Navy enlisted group. 30. Dyer, F. N., & Hlilligoss, R. Z. Using an assessment center to predict field leadership performance of Army

Prediction of contact mechanics in metal-on-metal Total Hip Replacement for parametrically comprehensive designs and loads.

Science.gov (United States)

Donaldson, Finn E; Nyman, Edward; Coburn, James C

2015-07-16

Manufacturers and investigators of Total Hip Replacement (THR) bearings require tools to predict the contact mechanics resulting from diverse design and loading parameters. This study provides contact mechanics solutions for metal-on-metal (MoM) bearings that encompass the current design space and could aid pre-clinical design optimization and evaluation. Stochastic finite element (FE) simulation was used to calculate the head-on-cup contact mechanics for five thousand combinations of design and loading parameters. FE results were used to train a Random Forest (RF) surrogate model to rapidly predict the contact patch dimensions, contact area, pressures and plastic deformations for arbitrary designs and loading. In addition to widely observed polar and edge contact, FE results included ring-polar, asymmetric-polar, and transitional categories which have previously received limited attention. Combinations of design and load parameters associated with each contact category were identified. Polar contact pressures were predicted in the range of 0-200 MPa with no permanent deformation. Edge loading (with subluxation) was associated with pressures greater than 500 MPa and induced permanent deformation in 83% of cases. Transitional-edge contact (with little subluxation) was associated with intermediate pressures and permanent deformation in most cases, indicating that, even with ideal anatomical alignment, bearings may face extreme wear challenges. Surrogate models were able to accurately predict contact mechanics 18,000 times faster than FE analyses. The developed surrogate models enable rapid prediction of MoM bearing contact mechanics across the most comprehensive range of loading and designs to date, and may be useful to those performing bearing design optimization or evaluation. Published by Elsevier Ltd.

A statistical approach to nuclear fuel design and performance

Science.gov (United States)

Cunning, Travis Andrew

As CANDU fuel failures can have significant economic and operational consequences on the Canadian nuclear power industry, it is essential that factors impacting fuel performance are adequately understood. Current industrial practice relies on deterministic safety analysis and the highly conservative "limit of operating envelope" approach, where all parameters are assumed to be at their limits simultaneously. This results in a conservative prediction of event consequences with little consideration given to the high quality and precision of current manufacturing processes. This study employs a novel approach to the prediction of CANDU fuel reliability. Probability distributions are fitted to actual fuel manufacturing datasets provided by Cameco Fuel Manufacturing, Inc. They are used to form input for two industry-standard fuel performance codes: ELESTRES for the steady-state case and ELOCA for the transient case---a hypothesized 80% reactor outlet header break loss of coolant accident. Using a Monte Carlo technique for input generation, 105 independent trials are conducted and probability distributions are fitted to key model output quantities. Comparing model output against recognized industrial acceptance criteria, no fuel failures are predicted for either case. Output distributions are well removed from failure limit values, implying that margin exists in current fuel manufacturing and design. To validate the results and attempt to reduce the simulation burden of the methodology, two dimensional reduction methods are assessed. Using just 36 trials, both methods are able to produce output distributions that agree strongly with those obtained via the brute-force Monte Carlo method, often to a relative discrepancy of less than 0.3% when predicting the first statistical moment, and a relative discrepancy of less than 5% when predicting the second statistical moment. In terms of global sensitivity, pellet density proves to have the greatest impact on fuel performance

Identification of the Predictive Power of Five Factor Personality Traits for Individual Instrument Performance Anxiety

Science.gov (United States)

Özdemir, Gökhan; Dalkiran, Esra

2017-01-01

This study, with the aim of identifying the predictive power of the five-factor personality traits of music teacher candidates on individual instrument performance anxiety, was designed according to the relational screening model. The study population was students attending the Music Education branch of Fine Arts Education Departments in…

Performance of local information-based link prediction: a sampling perspective

Science.gov (United States)

Zhao, Jichang; Feng, Xu; Dong, Li; Liang, Xiao; Xu, Ke

2012-08-01

Link prediction is pervasively employed to uncover the missing links in the snapshots of real-world networks, which are usually obtained through different kinds of sampling methods. In the previous literature, in order to evaluate the performance of the prediction, known edges in the sampled snapshot are divided into the training set and the probe set randomly, without considering the underlying sampling approaches. However, different sampling methods might lead to different missing links, especially for the biased ways. For this reason, random partition-based evaluation of performance is no longer convincing if we take the sampling method into account. In this paper, we try to re-evaluate the performance of local information-based link predictions through sampling method governed division of the training set and the probe set. It is interesting that we find that for different sampling methods, each prediction approach performs unevenly. Moreover, most of these predictions perform weakly when the sampling method is biased, which indicates that the performance of these methods might have been overestimated in the prior works.

Prediction of the surface roughness of AA6082 flow-formed tubes by design of experiments

International Nuclear Information System (INIS)

Srinivasulu, M.; Komaraiah, M.; Rao, C. S. Krishna Prasada

2013-01-01

Flow forming is a modern, chipless metal forming process that is employed for the production of thin-walled seamless tubes. Experiments are conducted on AA6082 alloy pre-forms to flow form into thin-walled tubes on a CNC flow-forming machine with a single roller. Design of experiments is used to predict the surface roughness of flow-formed tubes. The process parameters selected for this study are the roller axial feed, mandrel speed, and roller radius. A standard response surface methodology (RSM) called the Box Behnken design is used to perform the experimental runs. The regression model developed by RSM successfully predicts the surface roughness of AA6082 flow-formed tubes within the range of the selected process parameters.

Prediction of the surface roughness of AA6082 flow-formed tubes by design of experiments

Energy Technology Data Exchange (ETDEWEB)

Srinivasulu, M. [Government Polytechnic for Women Badangpet, Hyderabad (India); Komaraiah, M. [Sreenidhi Institute of Science and Technology, Hyderabad (India); Rao, C. S. Krishna Prasada [Bharat Dynamics Limited, Hyderabad (India)

2013-06-15

Flow forming is a modern, chipless metal forming process that is employed for the production of thin-walled seamless tubes. Experiments are conducted on AA6082 alloy pre-forms to flow form into thin-walled tubes on a CNC flow-forming machine with a single roller. Design of experiments is used to predict the surface roughness of flow-formed tubes. The process parameters selected for this study are the roller axial feed, mandrel speed, and roller radius. A standard response surface methodology (RSM) called the Box Behnken design is used to perform the experimental runs. The regression model developed by RSM successfully predicts the surface roughness of AA6082 flow-formed tubes within the range of the selected process parameters.

PGT: A Statistical Approach to Prediction and Mechanism Design

Science.gov (United States)

Wolpert, David H.; Bono, James W.

One of the biggest challenges facing behavioral economics is the lack of a single theoretical framework that is capable of directly utilizing all types of behavioral data. One of the biggest challenges of game theory is the lack of a framework for making predictions and designing markets in a manner that is consistent with the axioms of decision theory. An approach in which solution concepts are distribution-valued rather than set-valued (i.e. equilibrium theory) has both capabilities. We call this approach Predictive Game Theory (or PGT). This paper outlines a general Bayesian approach to PGT. It also presents one simple example to illustrate the way in which this approach differs from equilibrium approaches in both prediction and mechanism design settings.

Designing Prediction Tasks in a Mathematics Software Environment

Science.gov (United States)

Brunström, Mats; Fahlgren, Maria

2015-01-01

There is a recognised need in mathematics teaching for new kinds of tasks which exploit the affordances provided by new technology. This paper focuses on the design of prediction tasks to foster student reasoning about exponential functions in a mathematics software environment. It draws on the first iteration of a design based research study…

Predicting university performance in psychology: the role of previous performance and discipline-specific knowledge

OpenAIRE

Betts, LR; Elder, TJ; Hartley, J; Blurton, A

2008-01-01

Recent initiatives to enhance retention and widen participation ensure it is crucial to understand the factors that predict students' performance during their undergraduate degree. The present research used Structural Equation Modeling (SEM) to test three separate models that examined the extent to which British Psychology students' A-level entry qualifications predicted: (1) their performance in years 1-3 of their Psychology degree, and (2) their overall degree performance. Students' overall...

Predicting Subcontractor Performance Using Web-Based Evolutionary Fuzzy Neural Networks

Directory of Open Access Journals (Sweden)

Chien-Ho Ko

2013-01-01

Full Text Available Subcontractor performance directly affects project success. The use of inappropriate subcontractors may result in individual work delays, cost overruns, and quality defects throughout the project. This study develops web-based Evolutionary Fuzzy Neural Networks (EFNNs to predict subcontractor performance. EFNNs are a fusion of Genetic Algorithms (GAs, Fuzzy Logic (FL, and Neural Networks (NNs. FL is primarily used to mimic high level of decision-making processes and deal with uncertainty in the construction industry. NNs are used to identify the association between previous performance and future status when predicting subcontractor performance. GAs are optimizing parameters required in FL and NNs. EFNNs encode FL and NNs using floating numbers to shorten the length of a string. A multi-cut-point crossover operator is used to explore the parameter and retain solution legality. Finally, the applicability of the proposed EFNNs is validated using real subcontractors. The EFNNs are evolved using 22 historical patterns and tested using 12 unseen cases. Application results show that the proposed EFNNs surpass FL and NNs in predicting subcontractor performance. The proposed approach improves prediction accuracy and reduces the effort required to predict subcontractor performance, providing field operators with web-based remote access to a reliable, scientific prediction mechanism.

Predicting subcontractor performance using web-based Evolutionary Fuzzy Neural Networks.

Science.gov (United States)

Ko, Chien-Ho

2013-01-01

Subcontractor performance directly affects project success. The use of inappropriate subcontractors may result in individual work delays, cost overruns, and quality defects throughout the project. This study develops web-based Evolutionary Fuzzy Neural Networks (EFNNs) to predict subcontractor performance. EFNNs are a fusion of Genetic Algorithms (GAs), Fuzzy Logic (FL), and Neural Networks (NNs). FL is primarily used to mimic high level of decision-making processes and deal with uncertainty in the construction industry. NNs are used to identify the association between previous performance and future status when predicting subcontractor performance. GAs are optimizing parameters required in FL and NNs. EFNNs encode FL and NNs using floating numbers to shorten the length of a string. A multi-cut-point crossover operator is used to explore the parameter and retain solution legality. Finally, the applicability of the proposed EFNNs is validated using real subcontractors. The EFNNs are evolved using 22 historical patterns and tested using 12 unseen cases. Application results show that the proposed EFNNs surpass FL and NNs in predicting subcontractor performance. The proposed approach improves prediction accuracy and reduces the effort required to predict subcontractor performance, providing field operators with web-based remote access to a reliable, scientific prediction mechanism.

Space Launch System Base Heating Test: Sub-Scale Rocket Engine/Motor Design, Development & Performance Analysis

Science.gov (United States)

Mehta, Manish; Seaford, Mark; Kovarik, Brian; Dufrene, Aaron; Solly, Nathan

2014-01-01

ATA-002 Technical Team has successfully designed, developed, tested and assessed the SLS Pathfinder propulsion systems for the Main Base Heating Test Program. Major Outcomes of the Pathfinder Test Program: Reach 90% of full-scale chamber pressure Achieved all engine/motor design parameter requirements Reach steady plume flow behavior in less than 35 msec Steady chamber pressure for 60 to 100 msec during engine/motor operation Similar model engine/motor performance to full-scale SLS system Mitigated nozzle throat and combustor thermal erosion Test data shows good agreement with numerical prediction codes Next phase of the ATA-002 Test Program Design & development of the SLS OML for the Main Base Heating Test Tweak BSRM design to optimize performance Tweak CS-REM design to increase robustness MSFC Aerosciences and CUBRC have the capability to develop sub-scale propulsion systems to meet desired performance requirements for short-duration testing.

Performance evaluation of an irreversible Miller cycle comparing FTT (finite-time thermodynamics) analysis and ANN (artificial neural network) prediction

International Nuclear Information System (INIS)

Mousapour, Ashkan; Hajipour, Alireza; Rashidi, Mohammad Mehdi; Freidoonimehr, Navid

2016-01-01

In this paper, the first and second-laws efficiencies are applied to performance analysis of an irreversible Miller cycle. In the irreversible cycle, the linear relation between the specific heat of the working fluid and its temperature, the internal irreversibility described using the compression and expansion efficiencies, the friction loss computed according to the mean velocity of the piston and the heat-transfer loss are considered. The effects of various design parameters, such as the minimum and maximum temperatures of the working fluid and the compression ratio on the power output and the first and second-laws efficiencies of the cycle are discussed. In the following, a procedure named ANN is used for predicting the thermal efficiency values versus the compression ratio, and the minimum and maximum temperatures of the Miller cycle. Nowadays, Miller cycle is widely used in the automotive industry and the obtained results of this study will provide some significant theoretical grounds for the design optimization of the Miller cycle. - Highlights: • The performance of an irreversible Miller cycle is investigated using FFT. • The effects of design parameters on the performance of the cycle are investigated. • ANN is applied to predict the thermal efficiency and the power output values. • There is an excellent correlation between FTT and ANN data. • ANN can be applied to predict data where FTT analysis has not been performed.

Modeling and design of a high-performance hybrid actuator

Science.gov (United States)

Aloufi, Badr; Behdinan, Kamran; Zu, Jean

2016-12-01

This paper presents the model and design of a novel hybrid piezoelectric actuator which provides high active and passive performances for smart structural systems. The actuator is composed of a pair of curved pre-stressed piezoelectric actuators, so-called commercially THUNDER actuators, installed opposite each other using two clamping mechanisms constructed of in-plane fixable hinges, grippers and solid links. A fully mathematical model is developed to describe the active and passive dynamics of the actuator and investigate the effects of its geometrical parameters on the dynamic stiffness, free displacement and blocked force properties. Among the literature that deals with piezoelectric actuators in which THUNDER elements are used as a source of electromechanical power, the proposed study is unique in that it presents a mathematical model that has the ability to predict the actuator characteristics and achieve other phenomena, such as resonances, mode shapes, phase shifts, dips, etc. For model validation, the measurements of the free dynamic response per unit voltage and passive acceleration transmissibility of a particular actuator design are used to check the accuracy of the results predicted by the model. The results reveal that there is a good agreement between the model and experiment. Another experiment is performed to teste the linearity of the actuator system by examining the variation of the output dynamic responses with varying forces and voltages at different frequencies. From the results, it can be concluded that the actuator acts approximately as a linear system at frequencies up to 1000 Hz. A parametric study is achieved here by applying the developed model to analyze the influence of the geometrical parameters of the fixable hinges on the active and passive actuator properties. The model predictions in the frequency range of 0-1000 Hz show that the hinge thickness, radius, and opening angle parameters have great effects on the frequency dynamic

Mental Strategies Predict Performance and Satisfaction with Performance among Soccer Players.

Science.gov (United States)

Kruk, Magdalena; Blecharz, Jan; Boberska, Monika; Zarychta, Karolina; Luszczynska, Aleksandra

2017-10-01

This study investigated the changes in mental strategies across the season and their effects on performance and satisfaction with individual performance. Data were collected three times: at the pre-season at Time 1 (T1; baseline), in the mid-season at Time 2 (T2; two-month follow-up), and at the end-of-season at Time 3 (T3; nine-month follow-up) among male soccer players (N = 97) aged 16-27. Athletes completed the questionnaires assessing the use of nine psychological strategies in competition and the level of satisfaction with individual performance. Endurance performance was measured objectively with a 300 m run. A high level of relaxation (T1) explained better 300 m run performance (T3) and a high level of self-talk explained a higher satisfaction with individual performance (T3). A rare use of distractibility and emotional control (T1) predicted a higher level of satisfaction with individual performance (T3). No predictive role of other psychological strategies was found. The use of emotional control, relaxation, and distractibility increased over the season, whereas the use of imagery and negative thinking declined. Besides the roles of self-talk, imagery, relaxation and goal-setting, the effects of distractibility and emotional control should be taken into account when considering athletes' mental training programs.

User's Self-Prediction of Performance in Motor Imagery Brain-Computer Interface.

Science.gov (United States)

Ahn, Minkyu; Cho, Hohyun; Ahn, Sangtae; Jun, Sung C

2018-01-01

Performance variation is a critical issue in motor imagery brain-computer interface (MI-BCI), and various neurophysiological, psychological, and anatomical correlates have been reported in the literature. Although the main aim of such studies is to predict MI-BCI performance for the prescreening of poor performers, studies which focus on the user's sense of the motor imagery process and directly estimate MI-BCI performance through the user's self-prediction are lacking. In this study, we first test each user's self-prediction idea regarding motor imagery experimental datasets. Fifty-two subjects participated in a classical, two-class motor imagery experiment and were asked to evaluate their easiness with motor imagery and to predict their own MI-BCI performance. During the motor imagery experiment, an electroencephalogram (EEG) was recorded; however, no feedback on motor imagery was given to subjects. From EEG recordings, the offline classification accuracy was estimated and compared with several questionnaire scores of subjects, as well as with each subject's self-prediction of MI-BCI performance. The subjects' performance predictions during motor imagery task showed a high positive correlation ( r = 0.64, p performance even without feedback information. This implies that the human brain is an active learning system and, by self-experiencing the endogenous motor imagery process, it can sense and adopt the quality of the process. Thus, it is believed that users may be able to predict MI-BCI performance and results may contribute to a better understanding of low performance and advancing BCI.

Using Mason number to predict MR damper performance from limited test data

Science.gov (United States)

Becnel, Andrew C.; Wereley, Norman M.

2017-05-01

The Mason number can be used to produce a single master curve which relates MR fluid stress versus strain rate behavior across a wide range of shear rates, temperatures, and applied magnetic fields. As applications of MR fluid energy absorbers expand to a variety of industries and operating environments, Mason number analysis offers a path to designing devices with desired performance from a minimal set of preliminary test data. Temperature strongly affects the off-state viscosity of the fluid, as the passive viscous force drops considerably at higher temperatures. Yield stress is not similarly affected, and stays relatively constant with changing temperature. In this study, a small model-scale MR fluid rotary energy absorber is used to measure the temperature correction factor of a commercially-available MR fluid from LORD Corporation. This temperature correction factor is identified from shear stress vs. shear rate data collected at four different temperatures. Measurements of the MR fluid yield stress are also obtained and related to a standard empirical formula. From these two MR fluid properties - temperature-dependent viscosity and yield stress - the temperature-corrected Mason number is shown to predict the force vs. velocity performance of a full-scale rotary MR fluid energy absorber. This analysis technique expands the design space of MR devices to high shear rates and allows for comprehensive predictions of overall performance across a wide range of operating conditions from knowledge only of the yield stress vs. applied magnetic field and a temperature-dependent viscosity correction factor.

Classifier-guided sampling for discrete variable, discontinuous design space exploration: Convergence and computational performance

Energy Technology Data Exchange (ETDEWEB)

Backlund, Peter B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Shahan, David W. [HRL Labs., LLC, Malibu, CA (United States); Seepersad, Carolyn Conner [Univ. of Texas, Austin, TX (United States)

2014-04-22

A classifier-guided sampling (CGS) method is introduced for solving engineering design optimization problems with discrete and/or continuous variables and continuous and/or discontinuous responses. The method merges concepts from metamodel-guided sampling and population-based optimization algorithms. The CGS method uses a Bayesian network classifier for predicting the performance of new designs based on a set of known observations or training points. Unlike most metamodeling techniques, however, the classifier assigns a categorical class label to a new design, rather than predicting the resulting response in continuous space, and thereby accommodates nondifferentiable and discontinuous functions of discrete or categorical variables. The CGS method uses these classifiers to guide a population-based sampling process towards combinations of discrete and/or continuous variable values with a high probability of yielding preferred performance. Accordingly, the CGS method is appropriate for discrete/discontinuous design problems that are ill-suited for conventional metamodeling techniques and too computationally expensive to be solved by population-based algorithms alone. In addition, the rates of convergence and computational properties of the CGS method are investigated when applied to a set of discrete variable optimization problems. Results show that the CGS method significantly improves the rate of convergence towards known global optima, on average, when compared to genetic algorithms.

MHTGR thermal performance envelopes: Reliability by design

International Nuclear Information System (INIS)

Etzel, K.T.; Howard, W.W.; Zgliczynski, J.B.

1992-05-01

This document discusses thermal performance envelopes which are used to specify steady-state design requirements for the systems of the Modular High Temperature Gas-Cooled Reactor to maximize plant performance reliability with optimized design. The thermal performance envelopes are constructed around the expected operating point accounting for uncertainties in actual plant as-built parameters and plant operation. The components are then designed to perform successfully at all points within the envelope. As a result, plant reliability is maximized by accounting for component thermal performance variation in the design. The design is optimized by providing a means to determine required margins in a disciplined and visible fashion

When predictions take control: The effect of task predictions on task switching performance

Directory of Open Access Journals (Sweden)

Wout eDuthoo

2012-08-01

Full Text Available In this paper, we aimed to investigate the role of self-generated predictions in the flexible control of behaviour. Therefore, we ran a task switching experiment in which participants were asked to try to predict the upcoming task in three conditions varying in switch rate (30%, 50% and 70%. Irrespective of their predictions, the colour of the target indicated which task participants had to perform. In line with previous studies (Mayr, 2006; Monsell & Mizon, 2006, the switch cost was attenuated as the switch rate increased. Importantly, a clear task repetition bias was found in all conditions, yet the task repetition prediction rate dropped from 78% over 66% to 49% with increasing switch probability in the three conditions. Irrespective of condition, the switch cost was strongly reduced in expectation of a task alternation compared to the cost of an unexpected task alternation following repetition predictions. Hence, our data suggest that the reduction in the switch cost with increasing switch probability is caused by a diminished expectancy for the task to repeat. Taken together, this paper highlights the importance of predictions in the flexible control of behaviour, and suggests a crucial role for task repetition expectancy in the context-sensitive adjusting of task switching performance.

System Predicts Critical Runway Performance Parameters

Science.gov (United States)

Millen, Ernest W.; Person, Lee H., Jr.

1990-01-01

Runway-navigation-monitor (RNM) and critical-distances-process electronic equipment designed to provide pilot with timely and reliable predictive navigation information relating to takeoff, landing and runway-turnoff operations. Enables pilot to make critical decisions about runway maneuvers with high confidence during emergencies. Utilizes ground-referenced position data only to drive purely navigational monitor system independent of statuses of systems in aircraft.

Optimizing the fMRI data-processing pipeline using prediction and reproducibility performance metrics: I. A preliminary group analysis

DEFF Research Database (Denmark)

Strother, Stephen C.; Conte, Stephen La; Hansen, Lars Kai

2004-01-01

We argue that published results demonstrate that new insights into human brain function may be obscured by poor and/or limited choices in the data-processing pipeline, and review the work on performance metrics for optimizing pipelines: prediction, reproducibility, and related empirical Receiver......, temporal detrending, and between-subject alignment) in a group analysis of BOLD-fMRI scans from 16 subjects performing a block-design, parametric-static-force task. Large-scale brain networks were detected using a multivariate linear discriminant analysis (canonical variates analysis, CVA) that was tuned...... of baseline scans have constant, equal means, and this assumption was assessed with prediction metrics. Higher-order polynomial warps compared to affine alignment had only a minor impact on the performance metrics. We found that both prediction and reproducibility metrics were required for optimizing...

Thermodynamic performance simulation and concise formulas for triple-pressure reheat HRSG of gas–steam combined cycle under off-design condition

International Nuclear Information System (INIS)

Zhang, Guoqiang; Zheng, Jiongzhi; Yang, Yongping; Liu, Wenyi

2016-01-01

Highlights: • An off-design performance simulation of triple-pressure reheat HRSG is executed. • The bottoming cycle characteristics of energy transfer/conversion are analyzed. • Concise formulas for the off-design performance of bottoming cycle are proposed. • The accuracy of the formulas is verified under different load control strategies. • The errors of the formulas are generally within 1% at a load of 100–50%. - Abstract: Concise semi-theoretical, semi-empirical formulas are developed in this study to predict the off-design performance of the bottoming cycle of the gas–steam turbine combined cycle. The formulas merely refer to the key thermodynamic design parameters (full load parameters) of the bottoming cycle and off-design gas turbine exhaust temperature and flow, which are convenient in determining the overall performance of the bottoming cycle. First, a triple-pressure reheat heat recovery steam generator (HRSG) is modeled, and thermodynamic analysis is performed. Second, concise semi-theoretical, semi-empirical performance prediction formulas for the bottoming cycle are proposed through a comprehensive analysis of the heat transfer characteristics of the HRSG and the energy conversion characteristics of the steam turbine under the off-design condition. The concise formulas are found to be effective, i.e., fast, simple, and precise in obtaining the thermodynamic parameters for bottoming cycle efficiency, HRSG heat transfer capacity, HRSG efficiency, steam turbine power output, and steam turbine efficiency under the off-design condition. Accuracy is verified by comparing the concise formulas’ calculation results with the simulation results and practical operation data under different load control strategies. The calculation errors are within 1.5% (mainly less than 1% for both simulation and actual operation data) under combined cycle load (gas turbine load) ranging from 50% to 100%. However, accuracy declines sharply when the turbine

Supporting change processes in design: Complexity, prediction and reliability

Energy Technology Data Exchange (ETDEWEB)

Eckert, Claudia M. [Engineering Design Centre, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ (United Kingdom)]. E-mail: cme26@cam.ac.uk; Keller, Rene [Engineering Design Centre, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ (United Kingdom)]. E-mail: rk313@cam.ac.uk; Earl, Chris [Open University, Department of Design and Innovation, Walton Hall, Milton Keynes MK7 6AA (United Kingdom)]. E-mail: C.F.Earl@open.ac.uk; Clarkson, P. John [Engineering Design Centre, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ (United Kingdom)]. E-mail: pjc10@cam.ac.uk

2006-12-15

Change to existing products is fundamental to design processes. New products are often designed through change or modification to existing products. Specific parts or subsystems are changed to similar ones whilst others are directly reused. Design by modification applies particularly to safety critical products where the reuse of existing working parts and subsystems can reduce cost and risk. However change is rarely a matter of just reusing or modifying parts. Changing one part can propagate through the entire design leading to costly rework or jeopardising the integrity of the whole product. This paper characterises product change based on studies in the aerospace and automotive industry and introduces tools to aid designers in understanding the potential effects of change. Two ways of supporting designers are described: probabilistic prediction of the effects of change and visualisation of change propagation through product connectivities. Change propagation has uncertainties which are amplified by the choices designers make in practice as they implement change. Change prediction and visualisation is discussed with reference to complexity in three areas of product development: the structural backcloth of connectivities in the existing product (and its processes), the descriptions of the product used in design and the actions taken to carry out changes.

Optimization Design and Performance Analysis of a Pit Turbine with Ultralow Head

Directory of Open Access Journals (Sweden)

Chunxia Yang

2014-04-01

Full Text Available A developed pit turbine with ultralow head was optimization designed under the design head of about 2 meters to achieve the goal of improving the turbine unit's efficiency. At the same time, the turbine's synthetic characteristic curve was drawn to predict the turbine's overall performance. Navier-Stokes equations and SIMPLEC algorithm were used for pit turbine's whole flow passage numerical simulation of the 3D, steady, incompressible, turbulent flow field. Through the CFD numerical simulation, the influence to ultralow head turbine's performance was analyzed by runner blade's different setting angles and guide vane's different axes. Considering the hydraulic performance of various methods, the best blade's setting angle and guide vane's axis were chosen. The results show that, the turbine unit has the best performance on efficiency, hydraulic loss, and so forth, with the blade's setting angle 23° and the angle 72° between the guide vane and the centerline of unit, meeting the power station's design requirements. The development pit turbine with ultralow head shows the highest efficiency of 87.6% under condition of design head of 2.1 meters and design discharge of 10 m3/s. The energy performance of pit turbine with ultralow head was researched by the model test of GD-WS-35 turbine. The model turbine's characteristic curve was drawn. The model turbine's high efficiency area is wide and the efficiency changes mildly. The numerical simulation results are essentially consistent with the model test results, while the former one is slightly higher than the latter one. The error range is ±3%.

Ground motion prediction needs for nuclear engineering design

International Nuclear Information System (INIS)

Hadjian, A.H.

1985-01-01

The basic design philosophy of nuclear power plants stipulates that the risk to the public be as low as reasonably achievable. As a result of this philosophy, the seismic design of nuclear power plants has tended, over time, to diverge from that of other engineered structures. The emphasis at the present time is to specify ground motion at a nuclear facility site as realistically as possible and to design all safety-related structures to respond to the specified ground motion in the elastic range. The characteristics of this realistic design ground motion are discussed and present prediction needs identified

Designing performativity for mixed reality installations

Directory of Open Access Journals (Sweden)

Andrew Morrison

2010-07-01

Full Text Available This article takes up the concept of performativity prevalent in the humanities and applies it to the design of installation arts in mixed reality mode. Based on the design, development and public access to two specific works, the concept is related to a form of research by design. We argue that the concept of performativity may be further usefully employed in investigations (design and research, artistic and public into digital arts where complex intersections between concepts, technologies, dramaturgy, media and participant actions are in flux and together constitute the emergence and experience of a work. Theories of performativity are related to these two works in an argument that further suggests there is room in research by design to also include ‘performative design’. The article is the result of a wide-ranging interdisciplinary collaboration and aims to convey some sense of that in its reporting style, content and analysis.

Roots of Performance - Aided Design in Utzon´s design principles

DEFF Research Database (Denmark)

Parigi, Dario

2014-01-01

on paper, to an evolving paradigm where the increasing integration of parametric tools, performative analysis and computational methods is changing the way we learn and design. Its constitutive factors are: 1) embedded tectonics, 2) performance simulation 3) computational methods.......This paper discuss an emerging paradigm here identified as PAD, acronym of Performance-Aided Design, that aims at embracing complexity in the design process, and tackling it with digital tools. Computer Aided Design tools are gradually shifting from the mere translation of the work once carried...

Quantitative analysis and design of a spray aerosol inhaler. Part 2: improvements in mouthpiece performance.

Science.gov (United States)

Hindle, Michael; Longest, P Worth

2013-10-01

The objective of this study was to utilize previously identified critical design attributes for the capillary aerosol generator as a model spray inhaler in order to develop a second-generation device that minimized aerosol drug deposition in the mouthpiece. Computational fluid dynamics (CFD) predictive analysis of the critical design attributes indicated that turbulence intensity should be reduced and the effective mouthpiece diameter should be increased. Two second-generation inhaler mouthpieces meeting these specifications were manufactured and tested. The first device (Design 1) implemented a larger cross-sectional area in the mouthpiece and streamlined flow, whereas the second device (Design 2) used a perforated mouthpiece wall. An in vitro deposition study was performed to quantify the deposition of drug mass in the mouthpieces and connected induction ports, and the results were compared with the CFD predictions. The two second-generation mouthpieces reduced in vitro aerosol deposition from the original value of 7.8% to values of 2.1% (Device 1) and 4.3% (Device 2), without largely altering the induction port deposition. This was achieved by design alterations aimed at reducing turbulence intensity and increasing the effective mouthpiece diameter. CFD model predictions were in good agreement with the in vitro experimental data. A second-generation spray inhaler mouthpiece with low drug deposition was developed using a predictive CFD model and in vitro experiments. Applying this quantitative analysis and design methodology to medical devices, which is similar to the Quality by Design paradigm, could provide significant advantages compared with traditional approaches.

Off-design performance loss model for radial turbines with pivoting, variable-area stators

Science.gov (United States)

Meitner, P. L.; Glassman, A. J.

1980-01-01

An off-design performance loss model was developed for variable stator (pivoted vane), radial turbines through analytical modeling and experimental data analysis. Stator loss is determined by a viscous loss model; stator vane end-clearance leakage effects are determined by a clearance flow model. Rotor loss coefficient were obtained by analyzing the experimental data from a turbine rotor previously tested with six stators having throat areas from 20 to 144 percent of design area and were correlated with stator-to-rotor throat area ratio. An incidence loss model was selected to obtain best agreement with experimental results. Predicted turbine performance is compared with experimental results for the design rotor as well as with results for extended and cutback versions of the rotor. Sample calculations were made to show the effects of stator vane end-clearance leakage.

TRM performance prediction in Yucca Mountain welded tuff from linear cutter tests

International Nuclear Information System (INIS)

Gertsch, R.; Ozdemir, L.; Gertsch, L.

1992-01-01

Performance predictions were developed for tunnel boring machines operating in welded tuff for the construction of the experimental study facility and the potential nuclear waste repository at Yucca Mountain. The predictions were based on test data obtained from an extensive series of linear cutting tests performed on samples of Topopah Spring welded tuff from the Yucca Mountain Project site. Using the cutter force, spacing, and penetration data from the experimental program, the thrust, torque, power, and rate of penetration were estimated for a 25 ft diameter tunnel boring machine (TBM) operating in welded tuff. Guidelines were developed for the optimal design of the TBM cutterhead to achieve high production rates at the lowest possible excavation costs. The results show that the Topopah Spring welded tuff (TSw2) can be excavated at relatively high rates of advance with state-of-the-art TBMs. The results also show, however, that the TBM torque and power requirements will be higher than estimated based on rock physical properties and past tunneling experience in rock formations of similar strength

Performance samples on academic tasks : improving prediction of academic performance

NARCIS (Netherlands)

Tanilon, Jenny

2011-01-01

This thesis is about the development and validation of a performance-based test, labeled as Performance Samples on academic tasks in Education and Child Studies (PSEd). PSEd is designed to identify students who are most able to perform the academic tasks involved in an Education and Child Studies

Hydrogen Bond Basicity Prediction for Medicinal Chemistry Design.

Science.gov (United States)

Kenny, Peter W; Montanari, Carlos A; Prokopczyk, Igor M; Ribeiro, Jean F R; Sartori, Geraldo Rodrigues

2016-05-12

Hydrogen bonding is discussed in the context of medicinal chemistry design. Minimized molecular electrostatic potential (Vmin) is shown to be an effective predictor of hydrogen bond basicity (pKBHX), and predictive models are presented for a number of hydrogen bond acceptor types relevant to medicinal chemistry. The problems posed by the presence of nonequivalent hydrogen bond acceptor sites in molecular structures are addressed by using nonlinear regression to fit measured pKBHX to calculated Vmin. Predictions are made for hydrogen bond basicity of fluorine in situations where relevant experimental measurements are not available. It is shown how predicted pKBHX can be used to provide insight into the nature of bioisosterism and to profile heterocycles. Examples of pKBHX prediction for molecular structures with multiple, nonequivalent hydrogen bond acceptors are presented.

Predicting the Impacts of Intravehicular Displays on Driving Performance with Human Performance Modeling

Science.gov (United States)

Mitchell, Diane Kuhl; Wojciechowski, Josephine; Samms, Charneta

2012-01-01

A challenge facing the U.S. National Highway Traffic Safety Administration (NHTSA), as well as international safety experts, is the need to educate car drivers about the dangers associated with performing distraction tasks while driving. Researchers working for the U.S. Army Research Laboratory have developed a technique for predicting the increase in mental workload that results when distraction tasks are combined with driving. They implement this technique using human performance modeling. They have predicted workload associated with driving combined with cell phone use. In addition, they have predicted the workload associated with driving military vehicles combined with threat detection. Their technique can be used by safety personnel internationally to demonstrate the dangers of combining distracter tasks with driving and to mitigate the safety risks.

Development of rational design technique for frame steel structure combining seismic resistance and economic performance

International Nuclear Information System (INIS)

Kato, Motoki; Morishita, Kunihiro; Shimono, Masaki; Chuman, Yasuharu; Okafuji, Takashi; Monaka, Toshiaki

2015-01-01

Anti-seismic designs have been applied to plant support steel frames for years. Today, a rational structure that further improves seismic resistance and ensures economic performance is required in response to an increase of seismic load on the assumption of predicted future massive earthquakes. For satisfying this requirement, a steel frame design method that combines a steel frame weight minimizing method, which enables economic design through simultaneous minimization of multiple steel frame materials, and a seismic response control design technology that improves seismic resistance has been established. Its application in the design of real structures has been promoted. This paper gives an overview of this design technology and presents design examples to which this design technology is applied. (author)

Comparison of in-plant performance test data with analytic prediction of reactor safety system injection transient (U)

International Nuclear Information System (INIS)

Roy, B.N.; Neill, C.H. Jr.

1993-01-01

This paper compares the performance test data from injection transients for both of the subsystems of the Supplementary Safety System of the Savannah River Site production reactor with analytical predictions from an in-house thermal hydraulic computer code. The code was initially developed for design validation of the new Supplementary Safety System subsystem, but is shown to be equally capable of predicting the performance of the Supplementary Safety System existing subsystem even though the two subsystem transient injections have marked differences. The code itself was discussed and its validation using prototypic tests with simulated fluids was reported in an earlier paper (Roy and Nomm 1991)

Using Machine Learning to Predict Student Performance

OpenAIRE

Pojon, Murat

2017-01-01

This thesis examines the application of machine learning algorithms to predict whether a student will be successful or not. The specific focus of the thesis is the comparison of machine learning methods and feature engineering techniques in terms of how much they improve the prediction performance. Three different machine learning methods were used in this thesis. They are linear regression, decision trees, and naïve Bayes classification. Feature engineering, the process of modification ...

Response Surface Design Model to Predict Surface Roughness when Machining Hastelloy C-2000 using Uncoated Carbide Insert

International Nuclear Information System (INIS)

Razak, N H; Rahman, M M; Kadirgama, K

2012-01-01

This paper presents to develop of the response surface design model to predict the surface roughness for end-milling operation of Hastelloy C-2000 using uncoated carbide insert. Mathematical model is developed to study the effect of three input cutting parameters includes the feed rate, axial depth of cut and cutting speed. Design of experiments (DOE) was implemented with the aid of the statistical software package. Analysis of variance (ANOVA) has been performed to verify the fit and adequacy of the developed mathematical model. The result shows that the feed rate gave the more effect on the both prediction values of Ra compared to the cutting speed and axial depth of cut. SEM and EDX analyses were performed in different cutting conditions. It can be concluded that the feed rate and cutting force give the higher impact to influence the machining characteristics of surface roughness. Thus, the optimizing the cutting conditions are essential in order to improve the surface roughness in machining of Hastlelloy C-2000.

Design and performance of the main amplifier system for the National Ignition Facility

International Nuclear Information System (INIS)

Beullier, J; Erlandson, A; Grebot, E; Guenet, J; Guenet, M; Horvath, J; Jancaitis, K; Larson, D; Lawson, J; LeTouze, G; Maille, X; Manes, K; Marshall, C; Mengue, T; Moor, E; Payne, S; Pedrotti, L; Rotter, M; Seznec, S; Sutton, S; Zapata, L.

1999-01-01

This paper describes the design and performance of flashlamp-pumped, Nd:glass. Brewster-angle slab amplifiers intended to be deployed in the National Ignition Facility (NIF). To verify performance, we tested a full-size, three-slab-long, NIF prototype amplifier, which we believe to be the largest flashlamp-pumped Nd:glass amplifier ever assembled. Like the NIF amplifier design, this prototype amplifier had eight 40-cm-square apertures combined in a four-aperture-high by two-aperture-wide matrix. Specially-shaped reflectors, anti-reflective coatings on the blastshields, and preionized flashlamps were used to increase storage efficiency. Cooling gas was flowed over the flashlamps to remove waste pump heat and to accelerate thermal wavefront recovery. The prototype gain results are consistent with model predictions and provide high confidence in the final engineering design of the NIF amplifiers. Although the dimensions, internal positions, and shapes of the components in the NIF amplifiers will be slightly different from the prototype, these differences are small and should produce only slight differences in amplifier performance

Optimization of the gas turbine-modular helium reactor using statistical methods to maximize performance without compromising system design margins

International Nuclear Information System (INIS)

Lommers, L.J.; Parme, L.L.; Shenoy, A.S.

1995-07-01

This paper describes a statistical approach for determining the impact of system performance and design uncertainties on power plant performance. The objectives of this design approach are to ensure that adequate margin is provided, that excess margin is minimized, and that full advantage can be taken of unconsumed margin. It is applicable to any thermal system in which these factors are important. The method is demonstrated using the Gas Turbine Modular Helium Reactor as an example. The quantitative approach described allows the characterization of plant performance and the specification of the system design requirements necessary to achieve the desired performance with high confidence. Performance variations due to design evolution, inservice degradation, and basic performance uncertainties are considered. The impact of all performance variabilities is combined using Monte Carlo analysis to predict the range of expected operation

A Study of Performance in Low-Power Tokamak Reactor with Integrated Predictive Modeling Code

International Nuclear Information System (INIS)

Pianroj, Y.; Onjun, T.; Suwanna, S.; Picha, R.; Poolyarat, N.

2009-07-01

Full text: A fusion hybrid or a small fusion power output with low power tokamak reactor is presented as another useful application of nuclear fusion. Such tokamak can be used for fuel breeding, high-level waste transmutation, hydrogen production at high temperature, and testing of nuclear fusion technology components. In this work, an investigation of the plasma performance in a small fusion power output design is carried out using the BALDUR predictive integrated modeling code. The simulations of the plasma performance in this design are carried out using the empirical-based Mixed Bohm/gyro Bohm (B/gB) model, whereas the pedestal temperature model is based on magnetic and flow shear (δ α ρ ζ 2 ) stabilization pedestal width scaling. The preliminary results using this core transport model show that the central ion and electron temperatures are rather pessimistic. To improve the performance, the optimization approach are carried out by varying some parameters, such as plasma current and power auxiliary heating, which results in some improvement of plasma performance

Predicting Performance of a Face Recognition System Based on Image Quality

NARCIS (Netherlands)

Dutta, A.

2015-01-01

In this dissertation, we focus on several aspects of models that aim to predict performance of a face recognition system. Performance prediction models are commonly based on the following two types of performance predictor features: a) image quality features; and b) features derived solely from

Utilizing Machine Learning and Automated Performance Metrics to Evaluate Robot-Assisted Radical Prostatectomy Performance and Predict Outcomes.

Science.gov (United States)

Hung, Andrew J; Chen, Jian; Che, Zhengping; Nilanon, Tanachat; Jarc, Anthony; Titus, Micha; Oh, Paul J; Gill, Inderbir S; Liu, Yan

2018-05-01

Surgical performance is critical for clinical outcomes. We present a novel machine learning (ML) method of processing automated performance metrics (APMs) to evaluate surgical performance and predict clinical outcomes after robot-assisted radical prostatectomy (RARP). We trained three ML algorithms utilizing APMs directly from robot system data (training material) and hospital length of stay (LOS; training label) (≤2 days and >2 days) from 78 RARP cases, and selected the algorithm with the best performance. The selected algorithm categorized the cases as "Predicted as expected LOS (pExp-LOS)" and "Predicted as extended LOS (pExt-LOS)." We compared postoperative outcomes of the two groups (Kruskal-Wallis/Fisher's exact tests). The algorithm then predicted individual clinical outcomes, which we compared with actual outcomes (Spearman's correlation/Fisher's exact tests). Finally, we identified five most relevant APMs adopted by the algorithm during predicting. The "Random Forest-50" (RF-50) algorithm had the best performance, reaching 87.2% accuracy in predicting LOS (73 cases as "pExp-LOS" and 5 cases as "pExt-LOS"). The "pExp-LOS" cases outperformed the "pExt-LOS" cases in surgery time (3.7 hours vs 4.6 hours, p = 0.007), LOS (2 days vs 4 days, p = 0.02), and Foley duration (9 days vs 14 days, p = 0.02). Patient outcomes predicted by the algorithm had significant association with the "ground truth" in surgery time (p algorithm in predicting, were largely related to camera manipulation. To our knowledge, ours is the first study to show that APMs and ML algorithms may help assess surgical RARP performance and predict clinical outcomes. With further accrual of clinical data (oncologic and functional data), this process will become increasingly relevant and valuable in surgical assessment and training.

Thermal performance envelopes for MHTGRs - Reliability by design

International Nuclear Information System (INIS)

Etzel, K.T.; Howard, W.W.; Zgliczynski, J.

1992-01-01

Thermal performance envelopes are used to specify steady-state design requirements for the systems of the modular high-temperature gas-cooled reactor (MHTGR) to maximize plant performance reliability with optimized design. The thermal performance envelopes are constructed around the expected operating point to account for uncertainties in actual plant as-built parameters and plant operation. The components are then designed to perform successfully at all points within the envelope. As a result, plant reliability is maximized by accounting for component thermal performance variation in the design. The design is optimized by providing a means to determine required margins in a disciplined and visible fashion. This is accomplished by coordinating these requirements with the various system and component designers in the early stages of the design, applying the principles of total quality management. The design is challenged by the more complex requirements associated with a range of operating conditions, but in return, high probability of delivering reliable performance throughout the plant life is ensured

Enhancing pavement performance prediction models for the Illinois Tollway System

OpenAIRE

Laxmikanth Premkumar; William R. Vavrik

2016-01-01

Accurate pavement performance prediction represents an important role in prioritizing future maintenance and rehabilitation needs, and predicting future pavement condition in a pavement management system. The Illinois State Toll Highway Authority (Tollway) with over 2000 lane miles of pavement utilizes the condition rating survey (CRS) methodology to rate pavement performance. Pavement performance models developed in the past for the Illinois Department of Transportation (IDOT) are used by th...

Goal Setting and Expectancy Theory Predictions of Effort and Performance.

Science.gov (United States)

Dossett, Dennis L.; Luce, Helen E.

Neither expectancy (VIE) theory nor goal setting alone are effective determinants of individual effort and task performance. To test the combined ability of VIE and goal setting to predict effort and performance, 44 real estate agents and their managers completed questionnaires. Quarterly income goals predicted managers' ratings of agents' effort,…

Measuring and Predicting Sleep and Performance During Military Operations

Science.gov (United States)

2012-08-23

strengths of this modeling approach is that accurate predictions of fatigue, performance, or alert- ness can be made from observed sleep timing...and, in which fatigue, performance, or alertness predictions are required prior to the task. Limitations of Current Models The strengths and...mean ± SD, 35.9 ± 1.2 hours), crews flew to Auckland , New Zealand, where another short layover was un- dertaken (23.6 ± 0.95 hours). A final flight

Investigations of internal turbulent flows in a low-head tubular pump and its performance predictions

International Nuclear Information System (INIS)

Tang, X L; Chen, X S; Wang, F J; Yang, W; Wu, Y L

2012-01-01

Based on the RANS equations, standard k−ε turbulence model and SIMPLE algorithm, the internal turbulent flows in a low-head tubular pump were simulated by using the FLUENT software. Based on the predicted flow fields, the external performance curves including the head-discharge, efficiency-discharge and power-discharge curves were further obtained. The calculated results indicate that the internal flow pattern is smooth at the best efficiency point (BEP). When it works under off-design operating cases, the flow pattern inside the diffuser and the discharge passage is disorder, and at the same time, the hydraulic losses mainly come from the secondary flows. At large flow rates, the minimum static pressure near the inlet of the blade pressure surfaces due to the negative attack angle. At small flow rates, the minimum value happens near the inlet of the suction surfaces. At the BEP, the lowest static pressure appears in the region behind the suction surfaces inlet. The newly-designed model is validated by the comparisons between its predicted external performance and the experimental data of the JGM-3 model. This research provides some important references for the optimization of a low-head tubular pump.

Design study and performance analysis of a high-speed multistage variable-geometry fan for a variable cycle engine

Science.gov (United States)

Sullivan, T. J.; Parker, D. E.

1979-01-01

A design technology study was performed to identify a high speed, multistage, variable geometry fan configuration capable of achieving wide flow modulation with near optimum efficiency at the important operating condition. A parametric screening study of the front and rear block fans was conducted in which the influence of major fan design features on weight and efficiency was determined. Key design parameters were varied systematically to determine the fan configuration most suited for a double bypass, variable cycle engine. Two and three stage fans were considered for the front block. A single stage, core driven fan was studied for the rear block. Variable geometry concepts were evaluated to provide near optimum off design performance. A detailed aerodynamic design and a preliminary mechanical design were carried out for the selected fan configuration. Performance predictions were made for the front and rear block fans.

Methodologic Guide for Evaluating Clinical Performance and Effect of Artificial Intelligence Technology for Medical Diagnosis and Prediction.

Science.gov (United States)

Park, Seong Ho; Han, Kyunghwa

2018-03-01

The use of artificial intelligence in medicine is currently an issue of great interest, especially with regard to the diagnostic or predictive analysis of medical images. Adoption of an artificial intelligence tool in clinical practice requires careful confirmation of its clinical utility. Herein, the authors explain key methodology points involved in a clinical evaluation of artificial intelligence technology for use in medicine, especially high-dimensional or overparameterized diagnostic or predictive models in which artificial deep neural networks are used, mainly from the standpoints of clinical epidemiology and biostatistics. First, statistical methods for assessing the discrimination and calibration performances of a diagnostic or predictive model are summarized. Next, the effects of disease manifestation spectrum and disease prevalence on the performance results are explained, followed by a discussion of the difference between evaluating the performance with use of internal and external datasets, the importance of using an adequate external dataset obtained from a well-defined clinical cohort to avoid overestimating the clinical performance as a result of overfitting in high-dimensional or overparameterized classification model and spectrum bias, and the essentials for achieving a more robust clinical evaluation. Finally, the authors review the role of clinical trials and observational outcome studies for ultimate clinical verification of diagnostic or predictive artificial intelligence tools through patient outcomes, beyond performance metrics, and how to design such studies. © RSNA, 2018.

Prediction of performance and evaluation of flexible pavement rehabilitation strategies

Directory of Open Access Journals (Sweden)

Kang-Won Wayne Lee

2017-04-01

Full Text Available Five test sections with different additives and strategies were established to rehabilitate a State-maintained highway more effectively in Rhode Island (RI: control, calcium chloride, asphalt emulsion, Portland cement and geogrid. Resilient moduli of subgrade soils and subbase materials before and after full depth rehabilitation were employed as input parameters to predict the performance of pavement structures using AASHTOWare Pavement ME Design (Pavement ME software in terms of rutting, cracking and roughness. It was attempted to use Level 1 input (which includes traffic full spectrum data, climate data and structural layer properties for Pavement ME. Traffic data was obtained from a Weigh-in-Motion (WIM instrument and Providence station was used for collecting climatic data. Volumetric properties, dynamic modulus and creep compliance were used as input parameters for 19 mm (0.75 in. warm mix asphalt (WMA base and 12.5 mm (0.5 in. WMA surface layer. The results indicated that all test sections observed AC top-down (longitudinal cracking except Portland cement section which passed for all criteria. The order in terms of performance (best to worst for all test sections by Pavement ME was Portland cement, calcium chloride, control, geogrid, and asphalt emulsion. It was also observed that all test sections passed for both bottom up and top down fatigue cracking by increasing thickness of either of the two top asphalt layers. Test sections with five different base/subbase materials were evaluated in last two years through visual condition survey and measurements of deflection and roughness to confirm the prediction, but there was no serious distress and roughness. Thus these experiments allowed selecting the best rehabilitation/reconstruction techniques for the particular and/or similar highway, and a framework was formulated to select an optimal technique and/or strategy for future rehabilitation/reconstruction projects. Finally, guidelines for

Performance-based Pareto optimal design

NARCIS (Netherlands)

Sariyildiz, I.S.; Bittermann, M.S.; Ciftcioglu, O.

2008-01-01

A novel approach for performance-based design is presented, where Pareto optimality is pursued. Design requirements may contain linguistic information, which is difficult to bring into computation or make consistent their impartial estimations from case to case. Fuzzy logic and soft computing are

Enhancing pavement performance prediction models for the Illinois Tollway System

Directory of Open Access Journals (Sweden)

Laxmikanth Premkumar

2016-01-01

Full Text Available Accurate pavement performance prediction represents an important role in prioritizing future maintenance and rehabilitation needs, and predicting future pavement condition in a pavement management system. The Illinois State Toll Highway Authority (Tollway with over 2000 lane miles of pavement utilizes the condition rating survey (CRS methodology to rate pavement performance. Pavement performance models developed in the past for the Illinois Department of Transportation (IDOT are used by the Tollway to predict the future condition of its network. The model projects future CRS ratings based on pavement type, thickness, traffic, pavement age and current CRS rating. However, with time and inclusion of newer pavement types there was a need to calibrate the existing pavement performance models, as well as, develop models for newer pavement types.This study presents the results of calibrating the existing models, and developing new models for the various pavement types in the Illinois Tollway network. The predicted future condition of the pavements is used in estimating its remaining service life to failure, which is of immediate use in recommending future maintenance and rehabilitation requirements for the network. Keywords: Pavement performance models, Remaining life, Pavement management

Nuclear fuel elements design, fabrication and performance

CERN Document Server

Frost, Brian R T

1982-01-01

Nuclear Fuel Elements: Design, Fabrication and Performance is concerned with the design, fabrication, and performance of nuclear fuel elements, with emphasis on fast reactor fuel elements. Topics range from fuel types and the irradiation behavior of fuels to cladding and duct materials, fuel element design and modeling, fuel element performance testing and qualification, and the performance of water reactor fuels. Fast reactor fuel elements, research and test reactor fuel elements, and unconventional fuel elements are also covered. This volume consists of 12 chapters and begins with an overvie

DESIGN, PERFORMANCE, AND SUSTAINABILITY OF ENGINEERED COVERS FOR URANIUM MILL TAILINGS

Energy Technology Data Exchange (ETDEWEB)

Waugh, W. Jody

2004-04-21

Final remedies at most uranium mill tailings sites include engineered covers designed to contain metals and radionuclides in the subsurface for hundreds of years. Early cover designs rely on compacted soil layers to limit water infiltration and release of radon, but some of these covers inadvertently created habitats for deep-rooted plants. Root intrusion and soil development increased the saturated hydraulic conductivity several orders of magnitude above design targets. These covers may require high levels of maintenance to sustain long-term performance. Relatively low precipitation, high potential evapotranspiration, and thick unsaturated soils favor long-term hydrologic isolation of buried waste at arid and semiarid sites. Later covers were designed to mimic this natural soil-water balance with the goal of sustaining performance with little or no maintenance. For example, the cover for the Monticello, Utah, Superfund site relies on a thick soil-sponge layer overlying a sand-and-gravel capillary barrier to store precipitation while plants are dormant and on native vegetation to dry the soil sponge during the growing season. Measurements of both off-site caisson lysimeters and a large 3-ha lysimeter built into the final cover show that drainage has been well below a U.S. Environmental Protection Agency target of less than 3.0 mm/yr. Our stewardship strategy combines monitoring precursors to failure, probabilistic riskbased modeling, and characterization of natural analogs to project performance of covers for a range of possible future environmental scenarios. Natural analogs are needed to understand how ecological processes will influence cover performance, processes that cannot be predicted with short-term monitoring and existing numerical models.

Genomic Prediction of Testcross Performance in Canola (Brassica napus)

Science.gov (United States)

Jan, Habib U.; Abbadi, Amine; Lücke, Sophie; Nichols, Richard A.; Snowdon, Rod J.

2016-01-01

Genomic selection (GS) is a modern breeding approach where genome-wide single-nucleotide polymorphism (SNP) marker profiles are simultaneously used to estimate performance of untested genotypes. In this study, the potential of genomic selection methods to predict testcross performance for hybrid canola breeding was applied for various agronomic traits based on genome-wide marker profiles. A total of 475 genetically diverse spring-type canola pollinator lines were genotyped at 24,403 single-copy, genome-wide SNP loci. In parallel, the 950 F1 testcross combinations between the pollinators and two representative testers were evaluated for a number of important agronomic traits including seedling emergence, days to flowering, lodging, oil yield and seed yield along with essential seed quality characters including seed oil content and seed glucosinolate content. A ridge-regression best linear unbiased prediction (RR-BLUP) model was applied in combination with 500 cross-validations for each trait to predict testcross performance, both across the whole population as well as within individual subpopulations or clusters, based solely on SNP profiles. Subpopulations were determined using multidimensional scaling and K-means clustering. Genomic prediction accuracy across the whole population was highest for seed oil content (0.81) followed by oil yield (0.75) and lowest for seedling emergence (0.29). For seed yieId, seed glucosinolate, lodging resistance and days to onset of flowering (DTF), prediction accuracies were 0.45, 0.61, 0.39 and 0.56, respectively. Prediction accuracies could be increased for some traits by treating subpopulations separately; a strategy which only led to moderate improvements for some traits with low heritability, like seedling emergence. No useful or consistent increase in accuracy was obtained by inclusion of a population substructure covariate in the model. Testcross performance prediction using genome-wide SNP markers shows considerable

Design of a Clinical Decision Support System for Fracture Prediction Using Imbalanced Dataset

Directory of Open Access Journals (Sweden)

Yung-Fu Chen

2018-01-01

Full Text Available More than 1 billion people suffer from chronic respiratory diseases worldwide, accounting for more than 4 million deaths annually. Inhaled corticosteroid is a popular medication for treating chronic respiratory diseases. Its side effects include decreased bone mineral density and osteoporosis. The aims of this study are to investigate the association of inhaled corticosteroids and fracture and to design a clinical support system for fracture prediction. The data of patients aged 20 years and older, who had visited healthcare centers and been prescribed with inhaled corticosteroids within 2002–2010, were retrieved from the National Health Insurance Research Database (NHIRD. After excluding patients diagnosed with hip fracture or vertebrate fractures before using inhaled corticosteroid, a total of 11645 patients receiving inhaled corticosteroid therapy were included for this study. Among them, 1134 (9.7% were diagnosed with hip fracture or vertebrate fracture. The statistical results showed that demographic information, chronic respiratory diseases and comorbidities, and corticosteroid-related variables (cumulative dose, mean exposed daily dose, follow-up duration, and exposed duration were significantly different between fracture and nonfracture patients. The clinical decision support systems (CDSSs were designed with integrated genetic algorithm (GA and support vector machine (SVM by training and validating the models with balanced training sets obtained by random and cluster-based undersampling methods and testing with the imbalanced NHIRD dataset. Two different objective functions were adopted for obtaining optimal models with best predictive performance. The predictive performance of the CDSSs exhibits a sensitivity of 69.84–77.00% and an AUC of 0.7495–0.7590. It was concluded that long-term use of inhaled corticosteroids may induce osteoporosis and exhibit higher incidence of hip or vertebrate fractures. The accumulated dose of ICS and

On the increase of predictive performance with high-level data fusion

International Nuclear Information System (INIS)

Doeswijk, T.G.; Smilde, A.K.; Hageman, J.A.; Westerhuis, J.A.; Eeuwijk, F.A. van

2011-01-01

The combination of the different data sources for classification purposes, also called data fusion, can be done at different levels: low-level, i.e. concatenating data matrices, medium-level, i.e. concatenating data matrices after feature selection and high-level, i.e. combining model outputs. In this paper the predictive performance of high-level data fusion is investigated. Partial least squares is used on each of the data sets and dummy variables representing the classes are used as response variables. Based on the estimated responses y-hat j for data set j and class k, a Gaussian distribution p(g k |y-hat j ) is fitted. A simulation study is performed that shows the theoretical performance of high-level data fusion for two classes and two data sets. Within group correlations of the predicted responses of the two models and differences between the predictive ability of each of the separate models and the fused models are studied. Results show that the error rate is always less than or equal to the best performing subset and can theoretically approach zero. Negative within group correlations always improve the predictive performance. However, if the data sets have a joint basis, as with metabolomics data, this is not likely to happen. For equally performing individual classifiers the best results are expected for small within group correlations. Fusion of a non-predictive classifier with a classifier that exhibits discriminative ability lead to increased predictive performance if the within group correlations are strong. An example with real life data shows the applicability of the simulation results.

Probabilistic predictive modelling of carbon nanocomposites for medical implants design.

Science.gov (United States)

Chua, Matthew; Chui, Chee-Kong

2015-04-01

Modelling of the mechanical properties of carbon nanocomposites based on input variables like percentage weight of Carbon Nanotubes (CNT) inclusions is important for the design of medical implants and other structural scaffolds. Current constitutive models for the mechanical properties of nanocomposites may not predict well due to differences in conditions, fabrication techniques and inconsistencies in reagents properties used across industries and laboratories. Furthermore, the mechanical properties of the designed products are not deterministic, but exist as a probabilistic range. A predictive model based on a modified probabilistic surface response algorithm is proposed in this paper to address this issue. Tensile testing of three groups of different CNT weight fractions of carbon nanocomposite samples displays scattered stress-strain curves, with the instantaneous stresses assumed to vary according to a normal distribution at a specific strain. From the probabilistic density function of the experimental data, a two factors Central Composite Design (CCD) experimental matrix based on strain and CNT weight fraction input with their corresponding stress distribution was established. Monte Carlo simulation was carried out on this design matrix to generate a predictive probabilistic polynomial equation. The equation and method was subsequently validated with more tensile experiments and Finite Element (FE) studies. The method was subsequently demonstrated in the design of an artificial tracheal implant. Our algorithm provides an effective way to accurately model the mechanical properties in implants of various compositions based on experimental data of samples. Copyright © 2015 Elsevier Ltd. All rights reserved.

The steady performance prediction of propeller-rudder-bulb system based on potential iterative method

International Nuclear Information System (INIS)

Liu, Y B; Su, Y M; Ju, L; Huang, S L

2012-01-01

A new numerical method was developed for predicting the steady hydrodynamic performance of propeller-rudder-bulb system. In the calculation, the rudder and bulb was taken into account as a whole, the potential based surface panel method was applied both to propeller and rudder-bulb system. The interaction between propeller and rudder-bulb was taken into account by velocity potential iteration in which the influence of propeller rotation was considered by the average influence coefficient. In the influence coefficient computation, the singular value should be found and deleted. Numerical results showed that the method presented is effective for predicting the steady hydrodynamic performance of propeller-rudder system and propeller-rudder-bulb system. Comparing with the induced velocity iterative method, the method presented can save programming and calculation time. Changing dimensions, the principal parameter—bulb size that affect energy-saving effect was studied, the results show that the bulb on rudder have a optimal size at the design advance coefficient.

Hanford grout: predicting long-term performance

International Nuclear Information System (INIS)

Sewart, G.H.; Mitchell, D.H.; Treat, R.L.; McMakin, A.H.

1987-01-01

Grouted disposal is being planned for the low-level portion of liquid radioactive wastes at the Hanford site in Washington state. The performance of the disposal system must be such that it will protect people and the environment for thousands of years after disposal. To predict whether a specific grout disposal system will comply with existing and foreseen regulations, a performance assessment (PA) is performed. Long-term PAs are conducted for a range of performance conditions. Performance assessment is an inexact science. Quantifying projected impacts is especially difficult when only scant data exist on the behavior of certain components of the disposal system over thousands of years. To develop defensible results, we are honing the models and obtaining experimental data. The combination of engineered features and PA refinements is being used to ensure that Hanford grout will meet its principal goal: to protect people and the environment in the future

Predicting space telerobotic operator training performance from human spatial ability assessment

Science.gov (United States)

Liu, Andrew M.; Oman, Charles M.; Galvan, Raquel; Natapoff, Alan

2013-11-01

Our goal was to determine whether existing tests of spatial ability can predict an astronaut's qualification test performance after robotic training. Because training astronauts to be qualified robotics operators is so long and expensive, NASA is interested in tools that can predict robotics performance before training begins. Currently, the Astronaut Office does not have a validated tool to predict robotics ability as part of its astronaut selection or training process. Commonly used tests of human spatial ability may provide such a tool to predict robotics ability. We tested the spatial ability of 50 active astronauts who had completed at least one robotics training course, then used logistic regression models to analyze the correlation between spatial ability test scores and the astronauts' performance in their evaluation test at the end of the training course. The fit of the logistic function to our data is statistically significant for several spatial tests. However, the prediction performance of the logistic model depends on the criterion threshold assumed. To clarify the critical selection issues, we show how the probability of correct classification vs. misclassification varies as a function of the mental rotation test criterion level. Since the costs of misclassification are low, the logistic models of spatial ability and robotic performance are reliable enough only to be used to customize regular and remedial training. We suggest several changes in tracking performance throughout robotics training that could improve the range and reliability of predictive models.

Improving behavioral performance under full attention by adjusting response criteria to changes in stimulus predictability.

Science.gov (United States)

Katzner, Steffen; Treue, Stefan; Busse, Laura

2012-09-04

One of the key features of active perception is the ability to predict critical sensory events. Humans and animals can implicitly learn statistical regularities in the timing of events and use them to improve behavioral performance. Here, we used a signal detection approach to investigate whether such improvements in performance result from changes of perceptual sensitivity or rather from adjustments of a response criterion. In a regular sequence of briefly presented stimuli, human observers performed a noise-limited motion detection task by monitoring the stimulus stream for the appearance of a designated target direction. We manipulated target predictability through the hazard rate, which specifies the likelihood that a target is about to occur, given it has not occurred so far. Analyses of response accuracy revealed that improvements in performance could be accounted for by adjustments of the response criterion; a growing hazard rate was paralleled by an increasing tendency to report the presence of a target. In contrast, the hazard rate did not affect perceptual sensitivity. Consistent with previous research, we also found that reaction time decreases as the hazard rate grows. A simple rise-to-threshold model could well describe this decrease and attribute predictability effects to threshold adjustments rather than changes in information supply. We conclude that, even under conditions of full attention and constant perceptual sensitivity, behavioral performance can be optimized by dynamically adjusting the response criterion to meet ongoing changes in the likelihood of a target.

Selection of Prediction Methods for Thermophysical Properties for Process Modeling and Product Design of Biodiesel Manufacturing

DEFF Research Database (Denmark)

Su, Yung-Chieh; Liu, Y. A.; Díaz Tovar, Carlos Axel

2011-01-01

To optimize biodiesel manufacturing, many reported studies have built simulation models to quantify the relationship between operating conditions and process performance. For mass and energy balance simulations, it is essential to know the four fundamental thermophysical properties of the feed oil...... prediction methods on our group Web site (www.design.che.vt.edu) for the reader to download without charge....

A new model for predicting performance of fin-and-tube heat exchanger under frost condition

International Nuclear Information System (INIS)

Cui, J.; Li, W.Z.; Liu, Y.; Zhao, Y.S.

2011-01-01

Accurate prediction of frost characteristics has crucial influence on designing effective heat exchangers. In this paper, a new CFD (Computational Fluid Dynamics) model has been proposed to predict the frost behaviour. The initial period of frost formation can be predicted and the influence of surface structure can be considered. The numerical simulations have been carried out to investigate the performance of fin-and-tube heat exchanger under frost condition. The results have been validated by comparison of simulations with the data computed by empirical formulas. The transient local frost formation has been obtained. The average frost thickness, heat exchanger coefficient and pressure drop on air side has been analysed as well. In addition, the influence factors have also been discussed, such as fin pitch, relative humidity, air flow rate and evaporating temperature of refrigerant.

Gender Differences in Performance Predictions: Evidence from the Cognitive Reflection Test.

Science.gov (United States)

Ring, Patrick; Neyse, Levent; David-Barett, Tamas; Schmidt, Ulrich

2016-01-01

This paper studies performance predictions in the 7-item Cognitive Reflection Test (CRT) and whether they differ by gender. After participants completed the CRT, they predicted their own (i), the other participants' (ii), men's (iii), and women's (iv) number of correct answers. In keeping with existing literature, men scored higher on the CRT than women and both men and women were too optimistic about their own performance. When we compare gender-specific predictions, we observe that men think they perform significantly better than other men and do so significantly more than women. The equality between women's predictions about their own performance and their female peers cannot be rejected. Our findings contribute to the growing literature on the underpinnings of behavior in economics and in psychology by uncovering gender differences in confidence about one's ability relative to same and opposite sex peers.

Burst muscle performance predicts the speed, acceleration, and turning performance of Anna's hummingbirds.

Science.gov (United States)

Segre, Paolo S; Dakin, Roslyn; Zordan, Victor B; Dickinson, Michael H; Straw, Andrew D; Altshuler, Douglas L

2015-11-19

Despite recent advances in the study of animal flight, the biomechanical determinants of maneuverability are poorly understood. It is thought that maneuverability may be influenced by intrinsic body mass and wing morphology, and by physiological muscle capacity, but this hypothesis has not yet been evaluated because it requires tracking a large number of free flight maneuvers from known individuals. We used an automated tracking system to record flight sequences from 20 Anna's hummingbirds flying solo and in competition in a large chamber. We found that burst muscle capacity predicted most performance metrics. Hummingbirds with higher burst capacity flew with faster velocities, accelerations, and rotations, and they used more demanding complex turns. In contrast, body mass did not predict variation in maneuvering performance, and wing morphology predicted only the use of arcing turns and high centripetal accelerations. Collectively, our results indicate that burst muscle capacity is a key predictor of maneuverability.

Designing and Implementing Performance Technology for Teachers

Directory of Open Access Journals (Sweden)

Joi L. Moore

2004-06-01

Full Text Available This paper synthesizes research findings from a performance analysis of teacher tasks and the implementation of performance technology. These findings are aligned with design and implementation theories to provide understanding of the complex factors and events that occur during the implementation process. The article describes the necessary elements and conditions for designing and implementing performance tools in school environments that will encourage usage, efficient performance, and positive attitudes. Two models provide a visual representation of causal relationships between the implementation factors and the technology user. Although the implementation process can become complex because of the simultaneous events and phases, it can be properly managed through good communication and strategic involvement of teachers during the design and development process. The models may be able to assist technology designers and advocates with presenting innovations to teachers who are frequently asked to try technical solutions for performance support or improvement.

Predicting the seismic performance of typical R/C healthcare facilities: emphasis on hospitals

Science.gov (United States)

Bilgin, Huseyin; Frangu, Idlir

2017-09-01

Reinforced concrete (RC) type of buildings constitutes an important part of the current building stock in earthquake prone countries such as Albania. Seismic response of structures during a severe earthquake plays a vital role in the extent of structural damage and resulting injuries and losses. In this context, this study evaluates the expected performance of a five-story RC healthcare facility, representative of common practice in Albania, designed according to older codes. The design was based on the code requirements used in this region during the mid-1980s. Non-linear static and dynamic time history analyses were conducted on the structural model using the Zeus NL computer program. The dynamic time history analysis was conducted with a set of ground motions from real earthquakes. The building responses were estimated in global levels. FEMA 356 criteria were used to predict the seismic performance of the building. The structural response measures such as capacity curve and inter-story drift under the set of ground motions and pushover analyses results were compared and detailed seismic performance assessment was done. The main aim of this study is considering the application and methodology for the earthquake performance assessment of existing buildings. The seismic performance of the structural model varied significantly under different ground motions. Results indicate that case study building exhibit inadequate seismic performance under different seismic excitations. In addition, reasons for the poor performance of the building is discussed.

Microstructural design of magnesium alloys for elevated temperature performance

Science.gov (United States)

Bryan, Zachary Lee

Magnesium alloys are promising for automotive and aerospace applications requiring lightweight structural metals due to their high specific strength. Weight reductions through material substitution significantly improve fuel efficiency and reduce greenhouse gas emissions. Challenges to widespread integration of Mg alloys primarily result from their limited ductility and elevated temperature strength. This research presents a microstructurally-driven systems design approach to Mg alloy development for elevated temperature applications. The alloy properties that were targeted included creep resistance, elevated temperature strength, room temperature ductility, and material cost. To enable microstructural predictions during the design process, computational thermodynamics was utilized with a newly developed atomic mobility database for HCP-Mg. The mobilities for Mg self-diffusion, as well as Al, Ag, Sn, and Zn solute diffusion in HCP-Mg were optimized from available diffusion literature using DICTRA. The optimized mobility database was then validated using experimental diffusion couples. To limit dislocation creep mechanisms in the first design iteration, a microstructure consisting of Al solutes in solid solution and a fine dispersion of Mg2Sn precipitates was targeted. The development of strength and diffusion models informed by thermodynamic predictions of phase equilibria led to the selection of an optimum Mg-1.9at%Sn-1.5at%Al (TA) alloy for elevated temperature performance. This alloy was cast, solution treated based upon DICTRA homogenization simulations, and then aged. While the tensile and creep properties were competitive with conventional Mg alloys, the TA mechanical performance was ultimately limited because of abnormal grain growth that occurred during solution treatment and the basal Mg2Sn particle morphology. For the second design iteration, insoluble Mg2Si intermetallic particles were added to the TA alloy to provide enhanced grain boundary pinning

Designing Predictive Models for Beta-Lactam Allergy Using the Drug Allergy and Hypersensitivity Database.

Science.gov (United States)

Chiriac, Anca Mirela; Wang, Youna; Schrijvers, Rik; Bousquet, Philippe Jean; Mura, Thibault; Molinari, Nicolas; Demoly, Pascal

Beta-lactam antibiotics represent the main cause of allergic reactions to drugs, inducing both immediate and nonimmediate allergies. The diagnosis is well established, usually based on skin tests and drug provocation tests, but cumbersome. To design predictive models for the diagnosis of beta-lactam allergy, based on the clinical history of patients with suspicions of allergic reactions to beta-lactams. The study included a retrospective phase, in which records of patients explored for a suspicion of beta-lactam allergy (in the Allergy Unit of the University Hospital of Montpellier between September 1996 and September 2012) were used to construct predictive models based on a logistic regression and decision tree method; a prospective phase, in which we performed an external validation of the chosen models in patients with suspicion of beta-lactam allergy recruited from 3 allergy centers (Montpellier, Nîmes, Narbonne) between March and November 2013. Data related to clinical history and allergy evaluation results were retrieved and analyzed. The retrospective and prospective phases included 1991 and 200 patients, respectively, with a different prevalence of confirmed beta-lactam allergy (23.6% vs 31%, P = .02). For the logistic regression method, performances of the models were similar in both samples: sensitivity was 51% (vs 60%), specificity 75% (vs 80%), positive predictive value 40% (vs 57%), and negative predictive value 83% (vs 82%). The decision tree method reached a sensitivity of 29.5% (vs 43.5%), specificity of 96.4% (vs 94.9%), positive predictive value of 71.6% (vs 79.4%), and negative predictive value of 81.6% (vs 81.3%). Two different independent methods using clinical history predictors were unable to accurately predict beta-lactam allergy and replace a conventional allergy evaluation for suspected beta-lactam allergy. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Differential effects of two types of formative assessment in predicting performance of first-year medical students.

Science.gov (United States)

Krasne, Sally; Wimmers, Paul F; Relan, Anju; Drake, Thomas A

2006-05-01

Formative assessments are systematically designed instructional interventions to assess and provide feedback on students' strengths and weaknesses in the course of teaching and learning. Despite their known benefits to student attitudes and learning, medical school curricula have been slow to integrate such assessments into the curriculum. This study investigates how performance on two different modes of formative assessment relate to each other and to performance on summative assessments in an integrated, medical-school environment. Two types of formative assessment were administered to 146 first-year medical students each week over 8 weeks: a timed, closed-book component to assess factual recall and image recognition, and an un-timed, open-book component to assess higher order reasoning including the ability to identify and access appropriate resources and to integrate and apply knowledge. Analogous summative assessments were administered in the ninth week. Models relating formative and summative assessment performance were tested using Structural Equation Modeling. Two latent variables underlying achievement on formative and summative assessments could be identified; a "formative-assessment factor" and a "summative-assessment factor," with the former predicting the latter. A latent variable underlying achievement on open-book formative assessments was highly predictive of achievement on both open- and closed-book summative assessments, whereas a latent variable underlying closed-book assessments only predicted performance on the closed-book summative assessment. Formative assessments can be used as effective predictive tools of summative performance in medical school. Open-book, un-timed assessments of higher order processes appeared to be better predictors of overall summative performance than closed-book, timed assessments of factual recall and image recognition.

Predicting asthma in preschool children with asthma symptoms: study rationale and design

Directory of Open Access Journals (Sweden)

Hafkamp-de Groen Esther

2012-10-01

Full Text Available Abstract Background In well-child care it is difficult to determine whether preschool children with asthma symptoms actually have or will develop asthma at school age. The PIAMA (Prevention and Incidence of Asthma and Mite Allergy Risk Score has been proposed as an instrument that predicts asthma at school age, using eight easy obtainable parameters, assessed at the time of first asthma symptoms at preschool age. The aim of this study is to present the rationale and design of a study 1 to externally validate and update the PIAMA Risk Score, 2 to develop an Asthma Risk Appraisal Tool to predict asthma at school age in (specific subgroups of preschool children with asthma symptoms and 3 to test implementation of the Asthma Risk Appraisal Tool in well-child care. Methods and design The study will be performed within the framework of Generation R, a prospective multi-ethnic cohort study. In total, consent for postnatal follow-up was obtained from 7893 children, born between 2002 and 2006. At preschool age the PIAMA Risk Score will be assessed and used to predict asthma at school age. Discrimination (C-index and calibration will be assessed for the external validation. We will study whether the predictive ability of the PIAMA Risk Score can be improved by removing or adding predictors (e.g. preterm birth. The (updated PIAMA Risk Score will be converted to the Asthma Risk Appraisal Tool- to predict asthma at school age in preschool children with asthma symptoms. Additionally, we will conduct a pilot study to test implementation of the Asthma Risk Appraisal Tool in well-child care. Discussion Application of the Asthma Risk Appraisal Tool in well-child care will help to distinguish preschool children at high- and low-risk of developing asthma at school age when asthma symptoms appear. This study will increase knowledge about the validity of the PIAMA risk score and might improve risk assessment of developing asthma at school age in (specific subgroups

The robust model predictive control based on mixed H2/H∞ approach with separated performance formulations and its ISpS analysis

Science.gov (United States)

Li, Dewei; Li, Jiwei; Xi, Yugeng; Gao, Furong

2017-12-01

In practical applications, systems are always influenced by parameter uncertainties and external disturbance. Both the H2 performance and the H∞ performance are important for the real applications. For a constrained system, the previous designs of mixed H2/H∞ robust model predictive control (RMPC) optimise one performance with the other performance requirement as a constraint. But the two performances cannot be optimised at the same time. In this paper, an improved design of mixed H2/H∞ RMPC for polytopic uncertain systems with external disturbances is proposed to optimise them simultaneously. In the proposed design, the original uncertain system is decomposed into two subsystems by the additive character of linear systems. Two different Lyapunov functions are used to separately formulate the two performance indices for the two subsystems. Then, the proposed RMPC is designed to optimise both the two performances by the weighting method with the satisfaction of the H∞ performance requirement. Meanwhile, to make the design more practical, a simplified design is also developed. The recursive feasible conditions of the proposed RMPC are discussed and the closed-loop input state practical stable is proven. The numerical examples reflect the enlarged feasible region and the improved performance of the proposed design.

Gender Differences in Performance Predictions: Evidence from the Cognitive Reflection Test

Directory of Open Access Journals (Sweden)

Patrick Ring

2016-11-01

Full Text Available This paper studies performance predictions in the 7-item Cognitive Reflection Test (CRT and whether they differ by gender. After participants completed the CRT, they predicted their own (i, the other participants’ (ii, men’s (iii, and women’s (iv number of correct answers. In keeping with existing literature, men scored higher on the CRT than women and both men and women were too optimistic about their own performance. When we compare gender-specific predictions, we observe that men think they perform significantly better than other men and do so significantly more than women. The equality between women’s predictions about their own performance and their female peers cannot be rejected. Our findings contribute to the growing literature on the underpinnings of behavior in economics and in psychology by uncovering gender differences in confidence about one’s ability relative to same and opposite sex peers.

Design of high-performance parallelized gene predictors in MATLAB.

Science.gov (United States)

Rivard, Sylvain Robert; Mailloux, Jean-Gabriel; Beguenane, Rachid; Bui, Hung Tien

2012-04-10

This paper proposes a method of implementing parallel gene prediction algorithms in MATLAB. The proposed designs are based on either Goertzel's algorithm or on FFTs and have been implemented using varying amounts of parallelism on a central processing unit (CPU) and on a graphics processing unit (GPU). Results show that an implementation using a straightforward approach can require over 4.5 h to process 15 million base pairs (bps) whereas a properly designed one could perform the same task in less than five minutes. In the best case, a GPU implementation can yield these results in 57 s. The present work shows how parallelism can be used in MATLAB for gene prediction in very large DNA sequences to produce results that are over 270 times faster than a conventional approach. This is significant as MATLAB is typically overlooked due to its apparent slow processing time even though it offers a convenient environment for bioinformatics. From a practical standpoint, this work proposes two strategies for accelerating genome data processing which rely on different parallelization mechanisms. Using a CPU, the work shows that direct access to the MEX function increases execution speed and that the PARFOR construct should be used in order to take full advantage of the parallelizable Goertzel implementation. When the target is a GPU, the work shows that data needs to be segmented into manageable sizes within the GFOR construct before processing in order to minimize execution time.

Multi-objective optimization design and experimental investigation of centrifugal fan performance

Science.gov (United States)

Zhang, Lei; Wang, Songling; Hu, Chenxing; Zhang, Qian

2013-11-01

Current studies of fan performance optimization mainly focus on two aspects: one is to improve the blade profile, and another is only to consider the influence of single impeller structural parameter on fan performance. However, there are few studies on the comprehensive effect of the key parameters such as blade number, exit stagger angle of blade and the impeller outlet width on the fan performance. The G4-73 backward centrifugal fan widely used in power plants is selected as the research object. Based on orthogonal design and BP neural network, a model for predicting the centrifugal fan performance parameters is established, and the maximum relative errors of the total pressure and efficiency are 0.974% and 0.333%, respectively. Multi-objective optimization of total pressure and efficiency of the fan is conducted with genetic algorithm, and the optimum combination of impeller structural parameters is proposed. The optimized parameters of blade number, exit stagger angle of blade and the impeller outlet width are seperately 14, 43.9°, and 21 cm. The experiments on centrifugal fan performance and noise are conducted before and after the installation of the new impeller. The experimental results show that with the new impeller, the total pressure of fan increases significantly in total range of the flow rate, and the fan efficiency is improved when the relative flow is above 75%, also the high efficiency area is broadened. Additionally, in 65% -100% relative flow, the fan noise is reduced. Under the design operating condition, total pressure and efficiency of the fan are improved by 6.91% and 0.5%, respectively. This research sheds light on the considering of comprehensive effect of impeller structrual parameters on fan performance, and a new impeller can be designed to satisfy the engineering demand such as energy-saving, noise reduction or solving air pressure insufficiency for power plants.

The trickle-down effect of predictability: Secondary task performance benefits from predictability in the primary task.

Directory of Open Access Journals (Sweden)

Magdalena Ewa Król

Full Text Available Predictions optimize processing by reducing attentional resources allocation to expected or predictable sensory data. Our study demonstrates that these saved processing resources can be then used on concurrent stimuli, and in consequence improve their processing and encoding. We illustrate this "trickle-down" effect with a dual task, where the primary task varied in terms of predictability. The primary task involved detection of a pre-specified symbol that appeared at some point of a short video of a dot moving along a random, semi-predictable or predictable trajectory. The concurrent secondary task involved memorization of photographs representing either emotionally neutral or non-neutral (social or threatening content. Performance in the secondary task was measured by a memory test. We found that participants allocated more attention to unpredictable (random and semi-predictable stimuli than to predictable stimuli. Additionally, when the stimuli in the primary task were more predictable, participants performed better in the secondary task, as evidenced by higher sensitivity in the memory test. Finally, social or threatening stimuli were allocated more "looking time" and a larger number of saccades than neutral stimuli. This effect was stronger for the threatening stimuli than social stimuli. Thus, predictability of environmental input is used in optimizing the allocation of attentional resources, which trickles-down and benefits the processing of concurrent stimuli.

The trickle-down effect of predictability: Secondary task performance benefits from predictability in the primary task.

Science.gov (United States)

Król, Magdalena Ewa; Król, Michał

2017-01-01

Predictions optimize processing by reducing attentional resources allocation to expected or predictable sensory data. Our study demonstrates that these saved processing resources can be then used on concurrent stimuli, and in consequence improve their processing and encoding. We illustrate this "trickle-down" effect with a dual task, where the primary task varied in terms of predictability. The primary task involved detection of a pre-specified symbol that appeared at some point of a short video of a dot moving along a random, semi-predictable or predictable trajectory. The concurrent secondary task involved memorization of photographs representing either emotionally neutral or non-neutral (social or threatening) content. Performance in the secondary task was measured by a memory test. We found that participants allocated more attention to unpredictable (random and semi-predictable) stimuli than to predictable stimuli. Additionally, when the stimuli in the primary task were more predictable, participants performed better in the secondary task, as evidenced by higher sensitivity in the memory test. Finally, social or threatening stimuli were allocated more "looking time" and a larger number of saccades than neutral stimuli. This effect was stronger for the threatening stimuli than social stimuli. Thus, predictability of environmental input is used in optimizing the allocation of attentional resources, which trickles-down and benefits the processing of concurrent stimuli.

Comparison between design and actual energy performance of a HVAC-ground coupled heat pump system in cooling and heating operation

Energy Technology Data Exchange (ETDEWEB)

Magraner, T.; Quilis, S. [Energesis Ingenieria S.L., Ciudad Politecnica de la Innovacion, Camino de Vera s/n, 46022 Valencia (Spain); Montero, A. [Instituto de Ingenieria Energetica, Universidad Politecnica de Valencia, Camino de Vera s/n, 46022 Valencia (Spain); Urchueguia, J.F. [Instituto Universitario de Matematica Pura y Aplicada, Universidad Politecnica de Valencia, Camino de Vera s/n, 46022 Valencia (Spain)

2010-09-15

This work compares the experimental results obtained for the energy performance study of a ground coupled heat pump system with the design values predicted by means of standard methodology. The system energy performance of a monitored ground coupled heat pump system is calculated using the instantaneous measurements of temperature, flow and power consumption and these values are compared with the numerical predictions. These predictions are performed with the TRNSYS software tool following standard procedures taking the experimental thermal loads as input values. The main result of this work is that simulation results solely based on nominal heat pump capacities and performances overestimate the measured overall energy performance by a percentage between 15% and 20%. A sensitivity analysis of the simulation results to changes in percentage of its input parameters showed that the heat pump nominal coefficient of performance is the parameter that mostly affects the energy performance predictions. This analysis supports the idea that the discrepancies between experimental results and simulation outputs for this ground coupled system are mainly due to heat pump performance degradation for being used at partial load. An estimation of the impact of this effect in energy performance predictions reduces the discrepancies to values around 5%. (author)

Automatic performance estimation of conceptual temperature control system design for rapid development of real system

International Nuclear Information System (INIS)

Jang, Yu Jin

2013-01-01

This paper presents an automatic performance estimation scheme of conceptual temperature control system with multi-heater configuration prior to constructing the physical system for achieving rapid validation of the conceptual design. An appropriate low-order discrete-time model, which will be used in the controller design, is constructed after determining several basic factors including the geometric shape of controlled object and heaters, material properties, heater arrangement, etc. The proposed temperature controller, which adopts the multivariable GPC (generalized predictive control) scheme with scale factors, is then constructed automatically based on the above model. The performance of the conceptual temperature control system is evaluated by using a FEM (finite element method) simulation combined with the controller.

Automatic performance estimation of conceptual temperature control system design for rapid development of real system

Energy Technology Data Exchange (ETDEWEB)

Jang, Yu Jin [Dongguk University, GyeongJu (Korea, Republic of)

2013-07-15

This paper presents an automatic performance estimation scheme of conceptual temperature control system with multi-heater configuration prior to constructing the physical system for achieving rapid validation of the conceptual design. An appropriate low-order discrete-time model, which will be used in the controller design, is constructed after determining several basic factors including the geometric shape of controlled object and heaters, material properties, heater arrangement, etc. The proposed temperature controller, which adopts the multivariable GPC (generalized predictive control) scheme with scale factors, is then constructed automatically based on the above model. The performance of the conceptual temperature control system is evaluated by using a FEM (finite element method) simulation combined with the controller.

Predicting Mental Imagery-Based BCI Performance from Personality, Cognitive Profile and Neurophysiological Patterns.

Directory of Open Access Journals (Sweden)

Camille Jeunet

Full Text Available Mental-Imagery based Brain-Computer Interfaces (MI-BCIs allow their users to send commands to a computer using their brain-activity alone (typically measured by ElectroEncephaloGraphy-EEG, which is processed while they perform specific mental tasks. While very promising, MI-BCIs remain barely used outside laboratories because of the difficulty encountered by users to control them. Indeed, although some users obtain good control performances after training, a substantial proportion remains unable to reliably control an MI-BCI. This huge variability in user-performance led the community to look for predictors of MI-BCI control ability. However, these predictors were only explored for motor-imagery based BCIs, and mostly for a single training session per subject. In this study, 18 participants were instructed to learn to control an EEG-based MI-BCI by performing 3 MI-tasks, 2 of which were non-motor tasks, across 6 training sessions, on 6 different days. Relationships between the participants' BCI control performances and their personality, cognitive profile and neurophysiological markers were explored. While no relevant relationships with neurophysiological markers were found, strong correlations between MI-BCI performances and mental-rotation scores (reflecting spatial abilities were revealed. Also, a predictive model of MI-BCI performance based on psychometric questionnaire scores was proposed. A leave-one-subject-out cross validation process revealed the stability and reliability of this model: it enabled to predict participants' performance with a mean error of less than 3 points. This study determined how users' profiles impact their MI-BCI control ability and thus clears the way for designing novel MI-BCI training protocols, adapted to the profile of each user.

Performance and robustness of hybrid model predictive control for controllable dampers in building models

Science.gov (United States)

Johnson, Erik A.; Elhaddad, Wael M.; Wojtkiewicz, Steven F.

2016-04-01

A variety of strategies have been developed over the past few decades to determine controllable damping device forces to mitigate the response of structures and mechanical systems to natural hazards and other excitations. These "smart" damping devices produce forces through passive means but have properties that can be controlled in real time, based on sensor measurements of response across the structure, to dramatically reduce structural motion by exploiting more than the local "information" that is available to purely passive devices. A common strategy is to design optimal damping forces using active control approaches and then try to reproduce those forces with the smart damper. However, these design forces, for some structures and performance objectives, may achieve high performance by selectively adding energy, which cannot be replicated by a controllable damping device, causing the smart damper performance to fall far short of what an active system would provide. The authors have recently demonstrated that a model predictive control strategy using hybrid system models, which utilize both continuous and binary states (the latter to capture the switching behavior between dissipative and non-dissipative forces), can provide reductions in structural response on the order of 50% relative to the conventional clipped-optimal design strategy. This paper explores the robustness of this newly proposed control strategy through evaluating controllable damper performance when the structure model differs from the nominal one used to design the damping strategy. Results from the application to a two-degree-of-freedom structure model confirms the robustness of the proposed strategy.

Comparative values of medical school assessments in the prediction of internship performance.

Science.gov (United States)

Lee, Ming; Vermillion, Michelle

2018-02-01

Multiple undergraduate achievements have been used for graduate admission consideration. Their relative values in the prediction of residency performance are not clear. This study compared the contributions of major undergraduate assessments to the prediction of internship performance. Internship performance ratings of the graduates of a medical school were collected from 2012 to 2015. Hierarchical multiple regression analyses were used to examine the predictive values of undergraduate measures assessing basic and clinical sciences knowledge and clinical performances, after controlling for differences in the Medical College Admission Test (MCAT). Four hundred eighty (75%) graduates' archived data were used in the study. Analyses revealed that clinical competencies, assessed by the USMLE Step 2 CK, NBME medicine exam, and an eight-station objective structured clinical examination (OSCE), were strong predictors of internship performance. Neither the USMLE Step 1 nor the inpatient internal medicine clerkship evaluation predicted internship performance. The undergraduate assessments as a whole showed a significant collective relationship with internship performance (ΔR 2  = 0.12, p < 0.001). The study supports the use of clinical competency assessments, instead of pre-clinical measures, in graduate admission consideration. It also provides validity evidence for OSCE scores in the prediction of workplace performance.

Optimal Design of Low-Density SNP Arrays for Genomic Prediction: Algorithm and Applications.

Directory of Open Access Journals (Sweden)

Xiao-Lin Wu

Full Text Available Low-density (LD single nucleotide polymorphism (SNP arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for the optimal design of LD SNP chips. A multiple-objective, local optimization (MOLO algorithm was developed for design of optimal LD SNP chips that can be imputed accurately to medium-density (MD or high-density (HD SNP genotypes for genomic prediction. The objective function facilitates maximization of non-gap map length and system information for the SNP chip, and the latter is computed either as locus-averaged (LASE or haplotype-averaged Shannon entropy (HASE and adjusted for uniformity of the SNP distribution. HASE performed better than LASE with ≤1,000 SNPs, but required considerably more computing time. Nevertheless, the differences diminished when >5,000 SNPs were selected. Optimization was accomplished conditionally on the presence of SNPs that were obligated to each chromosome. The frame location of SNPs on a chip can be either uniform (evenly spaced or non-uniform. For the latter design, a tunable empirical Beta distribution was used to guide location distribution of frame SNPs such that both ends of each chromosome were enriched with SNPs. The SNP distribution on each chromosome was finalized through the objective function that was locally and empirically maximized. This MOLO algorithm was capable of selecting a set of approximately evenly-spaced and highly-informative SNPs, which in turn led to increased imputation accuracy compared with selection solely of evenly-spaced SNPs. Imputation accuracy increased with LD chip size, and imputation error rate was extremely low for chips with ≥3,000 SNPs. Assuming that genotyping or imputation error occurs at random, imputation error rate can be viewed as the upper limit for genomic prediction error. Our results show that about 25% of imputation error rate was propagated to genomic prediction in an Angus

Design-for-variety, postponement, and operational performance

DEFF Research Database (Denmark)

Boer, Henrike Engele Elisabeth

2015-01-01

Design for variety (DFV) practices such as product modularization, platform thinking and design for manufacturing/assembly have been suggested to yield considerable operational performance benefits. Some of these performance effects can be expected in all manufacturing settings, including the pos...

Micro-Vibration Performance Prediction of SEPTA24 Using SMeSim (RUAG Space Mechanism Simulator Tool)

Science.gov (United States)

Omiciuolo, Manolo; Lang, Andreas; Wismer, Stefan; Barth, Stephan; Szekely, Gerhard

2013-09-01

Scientific space missions are currently challenging the performances of their payloads. The performances can be dramatically restricted by micro-vibration loads generated by any moving parts of the satellites, thus by Solar Array Drive Assemblies too. Micro-vibration prediction of SADAs is therefore very important to support their design and optimization in the early stages of a programme. The Space Mechanism Simulator (SMeSim) tool, developed by RUAG, enhances the capability of analysing the micro-vibration emissivity of a Solar Array Drive Assembly (SADA) under a specified set of boundary conditions. The tool is developed in the Matlab/Simulink® environment throughout a library of blocks simulating the different components a SADA is made of. The modular architecture of the blocks, assembled by the user, and the set up of the boundary conditions allow time-domain and frequency-domain analyses of a rigid multi-body model with concentrated flexibilities and coupled- electronic control of the mechanism. SMeSim is used to model the SEPTA24 Solar Array Drive Mechanism and predict its micro-vibration emissivity. SMeSim and the return of experience earned throughout its development and use can now support activities like verification by analysis of micro-vibration emissivity requirements and/or design optimization to minimize the micro- vibration emissivity of a SADA.

Children's biological responsivity to acute stress predicts concurrent cognitive performance.

Science.gov (United States)

Roos, Leslie E; Beauchamp, Kathryn G; Giuliano, Ryan; Zalewski, Maureen; Kim, Hyoun K; Fisher, Philip A

2018-04-10

Although prior research has characterized stress system reactivity (i.e. hypothalamic-pituitary-adrenal axis, HPAA; autonomic nervous system, ANS) in children, it has yet to examine the extent to which biological reactivity predicts concurrent goal-directed behavior. Here, we employed a stressor paradigm that allowed concurrent assessment of both stress system reactivity and performance on a speeded-response task to investigate the links between biological reactivity and cognitive function under stress. We further investigated gender as a moderator given previous research suggesting that the ANS may be particularly predictive of behavior in males due to gender differences in socialization. In a sociodemographically diverse sample of young children (N = 58, M age = 5.38 yrs; 44% male), individual differences in sociodemographic covariates (age, household income), HPAA (i.e. cortisol), and ANS (i.e. respiratory sinus arrhythmia, RSA, indexing the parasympathetic branch; pre-ejection period, PEP, indexing the sympathetic branch) function were assessed as predictors of cognitive performance under stress. We hypothesized that higher income, older age, and greater cortisol reactivity would be associated with better performance overall, and flexible ANS responsivity (i.e. RSA withdrawal, PEP shortening) would be predictive of performance for males. Overall, females performed better than males. Two-group SEM analyses suggest that, for males, greater RSA withdrawal to the stressor was associated with better performance, while for females, older age, higher income, and greater cortisol reactivity were associated with better performance. Results highlight the relevance of stress system reactivity to cognitive performance under stress. Future research is needed to further elucidate for whom and in what situations biological reactivity predicts goal-directed behavior.

Perceived Medical School stress of undergraduate medical students predicts academic performance: an observational study.

Science.gov (United States)

Kötter, Thomas; Wagner, Josefin; Brüheim, Linda; Voltmer, Edgar

2017-12-16

Medical students are exposed to high amounts of stress. Stress and poor academic performance can become part of a vicious circle. In order to counteract this circularity, it seems important to better understand the relationship between stress and performance during medical education. The most widespread stress questionnaire designed for use in Medical School is the "Perceived Medical School Stress Instrument" (PMSS). It addresses a wide range of stressors, including workload, competition, social isolation and financial worries. Our aim was to examine the relation between the perceived Medical School stress of undergraduate medical students and academic performance. We measured Medical School stress using the PMSS at two different time points (at the end of freshman year and at the end of sophomore year) and matched stress scores together with age and gender to the first medical examination (M1) grade of the students (n = 456). PMSS scores from 2 and 14 months before M1 proved to be significant predictors for medical students' M1 grade. Age and gender also predict academic performance, making older female students with high stress scores a potential risk group for entering the vicious circle of stress and poor academic performance. PMSS sum scores 2 and 14 months before the M1 exam seem to have an independent predictive validity for medical students' M1 grade. More research is needed to identify potential confounders.

Design and implementation of predictive current control of three-phase PWM rectifier using space-vector modulation (SVM)

International Nuclear Information System (INIS)

Bouafia, Abdelouahab; Gaubert, Jean-Paul; Krim, Fateh

2010-01-01

This paper is concerned with the design and implementation of current control of three-phase PWM rectifier based on predictive control strategy. The proposed predictive current control technique operates with constant switching frequency, using space-vector modulation (SVM). The main goal of the designed current control scheme is to maintain the dc-bus voltage at the required level and to achieve the unity power factor (UPF) operation of the converter. For this purpose, two predictive current control algorithms, in the sense of deadbeat control, are developed for direct controlling input current vector of the converter in the stationary α-β and rotating d-q reference frame, respectively. For both predictive current control algorithms, at the beginning of each switching period, the required rectifier average voltage vector allowing the cancellation of both tracking errors of current vector components at the end of the switching period, is computed and applied during a predefined switching period by means of SVM. The main advantages of the proposed predictive current control are that no need to use hysteresis comparators or PI controllers in current control loops, and constant switching frequency. Finally, the developed predictive current control algorithms were tested both in simulations and experimentally, and illustrative results are presented here. Results have proven excellent performance in steady and transient states, and verify the validity of the proposed predictive current control which is compared to other control strategies.

Evaluation of icing drag coefficient correlations applied to iced propeller performance prediction

Science.gov (United States)

Miller, Thomas L.; Shaw, R. J.; Korkan, K. D.

1987-01-01

Evaluation of three empirical icing drag coefficient correlations is accomplished through application to a set of propeller icing data. The various correlations represent the best means currently available for relating drag rise to various flight and atmospheric conditions for both fixed-wing and rotating airfoils, and the work presented here ilustrates and evaluates one such application of the latter case. The origins of each of the correlations are discussed, and their apparent capabilities and limitations are summarized. These correlations have been made to be an integral part of a computer code, ICEPERF, which has been designed to calculate iced propeller performance. Comparison with experimental propeller icing data shows generally good agreement, with the quality of the predicted results seen to be directly related to the radial icing extent of each case. The code's capability to properly predict thrust coefficient, power coefficient, and propeller efficiency is shown to be strongly dependent on the choice of correlation selected, as well as upon proper specificatioon of radial icing extent.

Improved predictive modeling of white LEDs with accurate luminescence simulation and practical inputs with TracePro opto-mechanical design software

Science.gov (United States)

Tsao, Chao-hsi; Freniere, Edward R.; Smith, Linda

2009-02-01

The use of white LEDs for solid-state lighting to address applications in the automotive, architectural and general illumination markets is just emerging. LEDs promise greater energy efficiency and lower maintenance costs. However, there is a significant amount of design and cost optimization to be done while companies continue to improve semiconductor manufacturing processes and begin to apply more efficient and better color rendering luminescent materials such as phosphor and quantum dot nanomaterials. In the last decade, accurate and predictive opto-mechanical software modeling has enabled adherence to performance, consistency, cost, and aesthetic criteria without the cost and time associated with iterative hardware prototyping. More sophisticated models that include simulation of optical phenomenon, such as luminescence, promise to yield designs that are more predictive - giving design engineers and materials scientists more control over the design process to quickly reach optimum performance, manufacturability, and cost criteria. A design case study is presented where first, a phosphor formulation and excitation source are optimized for a white light. The phosphor formulation, the excitation source and other LED components are optically and mechanically modeled and ray traced. Finally, its performance is analyzed. A blue LED source is characterized by its relative spectral power distribution and angular intensity distribution. YAG:Ce phosphor is characterized by relative absorption, excitation and emission spectra, quantum efficiency and bulk absorption coefficient. Bulk scatter properties are characterized by wavelength dependent scatter coefficients, anisotropy and bulk absorption coefficient.

Predicting the effectiveness of road safety campaigns through alternative research designs.

Science.gov (United States)

Adamos, Giannis; Nathanail, Eftihia

2016-12-01

A large number of road safety communication campaigns have been designed and implemented in the recent years; however their explicit impact on driving behavior and road accident rates has been estimated in a rather low proportion. Based on the findings of the evaluation of three road safety communication campaigns addressing the issues of drinking and driving, seat belt usage, and driving fatigue, this paper applies different types of research designs (i.e., experimental, quasi-experimental, and non-experimental designs), when estimating the effectiveness of road safety campaigns, implements a cross-design assessment, and conducts a cross-campaign evaluation. An integrated evaluation plan was developed, taking into account the structure of evaluation questions, the definition of measurable variables, the separation of the target audience into intervention (exposed to the campaign) and control (not exposed to the campaign) groups, the selection of alternative research designs, and the appropriate data collection methods and techniques. Evaluating the implementation of different research designs in estimating the effectiveness of road safety campaigns, results showed that the separate pre-post samples design demonstrated better predictability than other designs, especially in data obtained from the intervention group after the realization of the campaign. The more constructs that were added to the independent variables, the higher the values of the predictability were. The construct that most affects behavior is intention, whereas the rest of the constructs have a lower impact on behavior. This is particularly significant in the Health Belief Model (HBM). On the other hand, behavioral beliefs, normative beliefs, and descriptive norms, are significant parameters for predicting intention according to the Theory of Planned Behavior (TPB). The theoretical and applied implications of alternative research designs and their applicability in the evaluation of road safety

Standardizing the performance evaluation of short-term wind prediction models

DEFF Research Database (Denmark)

Madsen, Henrik; Pinson, Pierre; Kariniotakis, G.

2005-01-01

Short-term wind power prediction is a primary requirement for efficient large-scale integration of wind generation in power systems and electricity markets. The choice of an appropriate prediction model among the numerous available models is not trivial, and has to be based on an objective...... evaluation of model performance. This paper proposes a standardized protocol for the evaluation of short-term wind-poser preciction systems. A number of reference prediction models are also described, and their use for performance comparison is analysed. The use of the protocol is demonstrated using results...... from both on-shore and off-shore wind forms. The work was developed in the frame of the Anemos project (EU R&D project) where the protocol has been used to evaluate more than 10 prediction systems....

Deep Recurrent Model for Server Load and Performance Prediction in Data Center

Directory of Open Access Journals (Sweden)

Zheng Huang

2017-01-01

Full Text Available Recurrent neural network (RNN has been widely applied to many sequential tagging tasks such as natural language process (NLP and time series analysis, and it has been proved that RNN works well in those areas. In this paper, we propose using RNN with long short-term memory (LSTM units for server load and performance prediction. Classical methods for performance prediction focus on building relation between performance and time domain, which makes a lot of unrealistic hypotheses. Our model is built based on events (user requests, which is the root cause of server performance. We predict the performance of the servers using RNN-LSTM by analyzing the log of servers in data center which contains user’s access sequence. Previous work for workload prediction could not generate detailed simulated workload, which is useful in testing the working condition of servers. Our method provides a new way to reproduce user request sequence to solve this problem by using RNN-LSTM. Experiment result shows that our models get a good performance in generating load and predicting performance on the data set which has been logged in online service. We did experiments with nginx web server and mysql database server, and our methods can been easily applied to other servers in data center.

The Performance of Step-Wise Group Screening Designs

Directory of Open Access Journals (Sweden)

M.M. Manene

2005-06-01

Full Text Available In this paper we evaluate the performance of step-wise group screening designs in which group-factors contain an equal number of factors in the initial step.  A usual assumption in group screening designs is that the directions of possible effects are known a-priori. In practice, however, this assumption is unreasonable. We shall examine step-wise group screening designs without errors in observations when this assumption is relaxed. We shall consider cancellations of effects within group-factors. The performance of step-wise group-screening designs shall then be compared with the performance of multistage group screening designs.

Predictive Validity of National Basketball Association Draft Combine on Future Performance.

Science.gov (United States)

Teramoto, Masaru; Cross, Chad L; Rieger, Randall H; Maak, Travis G; Willick, Stuart E

2018-02-01

Teramoto, M, Cross, CL, Rieger, RH, Maak, TG, and Willick, SE. Predictive validity of national basketball association draft combine on future performance. J Strength Cond Res 32(2): 396-408, 2018-The National Basketball Association (NBA) Draft Combine is an annual event where prospective players are evaluated in terms of their athletic abilities and basketball skills. Data collected at the Combine should help NBA teams select right the players for the upcoming NBA draft; however, its value for predicting future performance of players has not been examined. This study investigated predictive validity of the NBA Draft Combine on future performance of basketball players. We performed a principal component analysis (PCA) on the 2010-2015 Combine data to reduce correlated variables (N = 234), a correlation analysis on the Combine data and future on-court performance to examine relationships (maximum pairwise N = 217), and a robust principal component regression (PCR) analysis to predict first-year and 3-year on-court performance from the Combine measures (N = 148 and 127, respectively). Three components were identified within the Combine data through PCA (= Combine subscales): length-size, power-quickness, and upper-body strength. As per the correlation analysis, the individual Combine items for anthropometrics, including height without shoes, standing reach, weight, wingspan, and hand length, as well as the Combine subscale of length-size, had positive, medium-to-large-sized correlations (r = 0.313-0.545) with defensive performance quantified by Defensive Box Plus/Minus. The robust PCR analysis showed that the Combine subscale of length-size was a predictor most significantly associated with future on-court performance (p ≤ 0.05), including Win Shares, Box Plus/Minus, and Value Over Replacement Player, followed by upper-body strength. In conclusion, the NBA Draft Combine has value for predicting future performance of players.

Performance in grade 12 mathematics and science predicts student nurses' performance in first year science modules at a university in the Western Cape.

Science.gov (United States)

Mthimunye, Katlego D T; Daniels, Felicity M

2017-10-26

The demand for highly qualified and skilled nurses is increasing in South Africa as well as around the world. Having a background in science can create a significant advantage for students wishing to enrol for an undergraduate nursing qualification because nursing as profession is grounded in scientific evidence. The aim of this study was to investigate the predictive validity of grade 12 mathematics and science on the academic performance of first year student nurses in science modules. A quantitative research method using a cross-sectional predictive design was employed in this study. The participants included first year Bachelor of Nursing students enrolled at a university in the Western Cape, South Africa. Descriptive and inferential statistics were performed to analyse the data by using the IBM Statistical Package for Social Sciences versions 24. Descriptive analysis of all variables was performed as well as the Spearman's rank correlation test to describe the relationship among the study variables. Standard multiple linear regressions analysis was performed to determine the predictive validity of grade 12 mathematics and science on the academic performance of first year student nurses in science modules. The results of this study showed that grade 12 physical science is not a significant predictor (p > 0.062) of performance in first year science modules. The multiple linear regression revealed that grade 12 mathematics and life science grades explained 37.1% to 38.1% (R2 = 0.381 and adj R2 = 0.371) of the variation in the first year science grade distributions. Based on the results of the study it is evident that performance in grade 12 mathematics (β = 2.997) and life science (β = 3.175) subjects is a significant predictor (p < 0.001) of the performance in first year science modules for student nurses at the university identified for this study.

The predictive validity of the BioMedical Admissions Test for pre-clinical examination performance.

Science.gov (United States)

Emery, Joanne L; Bell, John F

2009-06-01

Some medical courses in the UK have many more applicants than places and almost all applicants have the highest possible previous and predicted examination grades. The BioMedical Admissions Test (BMAT) was designed to assist in the student selection process specifically for a number of 'traditional' medical courses with clear pre-clinical and clinical phases and a strong focus on science teaching in the early years. It is intended to supplement the information provided by examination results, interviews and personal statements. This paper reports on the predictive validity of the BMAT and its predecessor, the Medical and Veterinary Admissions Test. Results from the earliest 4 years of the test (2000-2003) were matched to the pre-clinical examination results of those accepted onto the medical course at the University of Cambridge. Correlation and logistic regression analyses were performed for each cohort. Section 2 of the test ('Scientific Knowledge') correlated more strongly with examination marks than did Section 1 ('Aptitude and Skills'). It also had a stronger relationship with the probability of achieving the highest examination class. The BMAT and its predecessor demonstrate predictive validity for the pre-clinical years of the medical course at the University of Cambridge. The test identifies important differences in skills and knowledge between candidates, not shown by their previous attainment, which predict their examination performance. It is thus a valid source of additional admissions information for medical courses with a strong scientific emphasis when previous attainment is very high.

Predictive testing of performance of metals in HTR service environments

International Nuclear Information System (INIS)

Kondo, T.; Shindo, M.; Tamura, M.; Tsuji, H.; Kurata, Y.; Tsukada, T.

1982-01-01

Status of the material testing in simulated HTGR environment is reviewed with special attention focused on the methodology of the prediction of performance in long time. Importance of controlling effective chemical potentials relations in the material-environmental interface is stressed in regard of the complex inter-dependent kinetic relation between oxidation and carbon transport. Based on the recent experimental observations, proposals are made to establish some procedures for conservative prediction of the metal performance

GLRS-R 2-colour retroreflector target design and predicted performance

Science.gov (United States)

Lund, Glenn

1993-01-01

This paper reports on the retroreflector ground-target design for the GLRS-R spaceborne dual-wavelength laser ranging system. The described passive design flows down from the requirements of high station autonomy, high global FOV (up to 60 degrees zenith angle), little or no multiple pulse returns, and adequate optical cross section for most ranging geometries. The proposed solution makes use of 5 hollow cube-corner retroreflectors of which one points to the zenith and the remaining four are inclined from the vertical at uniform azimuthal spacings. The need for fairly large (is approximately 10 cm) retroreflectors is expected (within turbulence limitations) to generate quite narrow diffraction lobes, thus placing non-trivial requirements on the vectorial accuracy of velocity aberration corrections. A good compromise solution is found by appropriately spoiling just one of the retroreflector dihedral angles from 90 degrees, thus generating two symmetrically oriented diffraction lobes in the return beam. The required spoil angles are found to have little dependence on ground target latitude. Various link budget analyses are presented, showing the influence of such factors as point-ahead optimization, turbulence, ranging angle, atmospheric visibility and ground target thermal deformations.

Application of propagation predictions to Earth/space telecommunications system design

Science.gov (United States)

1981-01-01

The corresponding between a given propagation phenomenon and system performance is considered. Propagation data are related to system performance parameters, allowing the systems engineer to perform the analyses determining how well requirements are met by a given system design, and enabling the systems engineer to modify that design if necessary. The various ways of specifying performance criteria for different kinds of systems are discussed, and a general procedure for system design is presented and demonstrated.

Containment design, performance criteria and research needs for advanced reactor designs

International Nuclear Information System (INIS)

Bagdi, G.; Ali, S.; Costello, J

2004-01-01

This paper points out some important shifts in the basic expectations in the performance requirements for containment structures and discusses the areas where the containment structure design requirements and acceptance criteria can be integrated with ultimate test based insights. Although there has not been any new reactor construction in the United States for over thirty years, several designs of evolutionary and advanced reactors have already been certified. Performance requirements for containment structures under design basis and severe accident conditions and explicit consideration of seismic margins have been used in the design certification process. In the United States, the containment structure design code is the American Society of Mechanical Engineers, Boiler and Pressure Vessel Code, Section III, Division 1, Subsection NE-Class MC for the steel containment and Section III, Division 2 for reinforced and prestressed concrete reactor vessels and containments. This containment design code was based on the early concept of applying design basis internal pressure and associated load combinations that included the operating basis and safe shutdown earthquake ground motion. These early design criteria served the nuclear industry and the regulatory authorities in maintaining public health and safety. However, these early design criteria do not incorporate the performance criteria related to containment function in an integrated fashion. Research in large scale model testing of containment structures to failure from over pressurization and shake table testing using simulated ground motion, have produced insights related to failure modes and material behavior at failure. The results of this research provide the opportunity to integrate these observations into design and acceptance criteria. This integration process would identify 'gaps' in the present knowledge and future research needs. This knowledge base is important for gleaning risk-informed insights into

Overview of Performance Based Practical Design

Science.gov (United States)

2018-03-01

DOI: https://doi.org/10.13023/KTC.RR.2018.03 State transportation agencies (STAs) have increasingly turned to practical design and performance based practical design(PBPD) to inform project development and implementation and to reduce project cos...

Scientific Performance Analysis of the SYZ Telescope Design versus the RC Telescope Design

Science.gov (United States)

Ma, Donglin; Cai, Zheng

2018-02-01

Recently, Su et al. propose an innovative design, referred as the “SYZ” design, for China’s new project of a 12 m optical-infrared telescope. The SYZ telescope design consists of three aspheric mirrors with non-zero power, including a relay mirror below the primary mirror. SYZ design yields a good imaging quality and has a relatively flat field curvature at Nasmyth focus. To evaluate the science-compatibility of this three-mirror telescope, in this paper, we thoroughly compare the performance of SYZ design with that of Ritchey–Chrétien (RC) design, a conventional two-mirror telescope design. Further, we propose the Observing Information Throughput (OIT) as a metric for quantitatively evaluating the telescopes’ science performance. We find that although a SYZ telescope yields a superb imaging quality over a large field of view, a two-mirror (RC) telescope design holds a higher overall throughput, a better diffraction-limited imaging quality in the central field of view (FOV < 5‧) which is better for the performance of extreme Adaptive Optics (AO), and a generally better scientific performance with a higher OIT value. D. Ma & Z. Cai contributed equally to this paper.

Predicting Performance with Contextualized Inventories, No Frame-of-reference Effect?

NARCIS (Netherlands)

Holtrop, D.J.; Born, M.P.; de Vries, R.E.

2014-01-01

A recent meta-analysis showed that contextualized personality inventories have incremental predictive validity over generic personality inventories when predicting job performance. This study aimed to investigate the differences between two types of contextualization of items: Adding an 'at work'

On the performance of a high head Francis turbine at design and off-design conditions

International Nuclear Information System (INIS)

Aakti, B; Amstutz, O; Casartelli, E; Romanelli, G; Mangani, L

2015-01-01

In the present paper, fully 360 degrees transient and steady-state simulations of a Francis turbine were performed at three operating conditions, namely at part load (PL), best efficiency point (BEP), and high load (HL), using different numerical approaches for the pressure-velocity coupling. The simulation domain includes the spiral casing with stay and guide vanes, the runner and the draft tube. The main target of the investigations is the numerical prediction of the overall performance of the high head Francis turbine model as well as local and integral quantities of the complete machine in different operating conditions. All results were compared with experimental data published by the workshop organization. All CFD simulations were performed at model scale with a new in-house, 3D, unstructured, object-oriented finite volume code within the framework of the open source OpenFOAM library. The novel fully coupled pressure-based solver is designed to solve the incompressible RANS- Equations and is capable of handling multiple references of frame (MRF). The obtained results show that the overall performance is well captured by the simulations. Regarding the local flow distributions within the inlet section of the draft-tube, the axial velocity is better estimated than the circumferential component

Sexual victimization history predicts academic performance in college women.

Science.gov (United States)

Baker, Majel R; Frazier, Patricia A; Greer, Christiaan; Paulsen, Jacob A; Howard, Kelli; Meredith, Liza N; Anders, Samantha L; Shallcross, Sandra L

2016-11-01

College women frequently report having experienced sexual victimization (SV) in their lifetime, including child sexual abuse and adolescent/adult sexual assault. Although the harmful mental health sequelae of SV have been extensively studied, recent research suggests that SV is also a risk factor for poorer college academic performance. The current studies examined whether exposure to SV uniquely predicted poorer college academic performance, even beyond contributions from three well-established predictors of academic performance: high school rank, composite standardized test scores (i.e., American College Testing [ACT]), and conscientiousness. Study 1 analyzed longitudinal data from a sample of female college students (N = 192) who were assessed at the beginning and end of one semester. SV predicted poorer cumulative end-of-semester grade point average (GPA) while controlling for well-established predictors of academic performance. Study 2 replicated these findings in a second longitudinal study of female college students (N = 390) and extended the analyses to include follow-up data on the freshmen and sophomore students (n = 206) 4 years later. SV predicted students' GPA in their final term at the university above the contributions of well-established academic predictors, and it was the only factor related to leaving college. These findings highlight the importance of expanding the scope of outcomes of SV to include academic performance, and they underscore the need to assess SV and other adverse experiences on college campuses to target students who may be at risk of poor performance or leaving college. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Bionic Design, Materials and Performance of Bone Tissue Scaffolds

Directory of Open Access Journals (Sweden)

Tong Wu

2017-10-01

Full Text Available Design, materials, and performance are important factors in the research of bone tissue scaffolds. This work briefly describes the bone scaffolds and their anatomic structure, as well as their biological and mechanical characteristics. Furthermore, we reviewed the characteristics of metal materials, inorganic materials, organic polymer materials, and composite materials. The importance of the bionic design in preoperative diagnosis models and customized bone scaffolds was also discussed, addressing both the bionic structure design (macro and micro structure and the bionic performance design (mechanical performance and biological performance. Materials and performance are the two main problems in the development of customized bone scaffolds. Bionic design is an effective way to solve these problems, which could improve the clinical application of bone scaffolds, by creating a balance between mechanical performance and biological performance.

Comparison and Prediction of Preclinical Students' Performance in ...

African Journals Online (AJOL)

olayemitoyin

The data support the hypothesis that students who performed well in one discipline were likely to .... predict success in the clinical curriculum (Baciewicz,. 1990). Similarly ... the International Association of Medical Science. Educators. 17-20.

Toward scalable parts families for predictable design of biological circuits.

Science.gov (United States)

Lucks, Julius B; Qi, Lei; Whitaker, Weston R; Arkin, Adam P

2008-12-01

Our current ability to engineer biological circuits is hindered by design cycles that are costly in terms of time and money, with constructs failing to operate as desired, or evolving away from the desired function once deployed. Synthetic biologists seek to understand biological design principles and use them to create technologies that increase the efficiency of the genetic engineering design cycle. Central to the approach is the creation of biological parts--encapsulated functions that can be composited together to create new pathways with predictable behaviors. We define five desirable characteristics of biological parts--independence, reliability, tunability, orthogonality and composability, and review studies of small natural and synthetic biological circuits that provide insights into each of these characteristics. We propose that the creation of appropriate sets of families of parts with these properties is a prerequisite for efficient, predictable engineering of new function in cells and will enable a large increase in the sophistication of genetic engineering applications.

Comparing theories' performance in predicting violence.

Science.gov (United States)

Haas, Henriette; Cusson, Maurice

2015-01-01

The stakes of choosing the best theory as a basis for violence prevention and offender rehabilitation are high. However, no single theory of violence has ever been universally accepted by a majority of established researchers. Psychiatry, psychology and sociology are each subdivided into different schools relying upon different premises. All theories can produce empirical evidence for their validity, some of them stating the opposite of each other. Calculating different models with multivariate logistic regression on a dataset of N = 21,312 observations and ninety-two influences allowed a direct comparison of the performance of operationalizations of some of the most important schools. The psychopathology model ranked as the best model in terms of predicting violence right after the comprehensive interdisciplinary model. Next came the rational choice and lifestyle model and third the differential association and learning theory model. Other models namely the control theory model, the childhood-trauma model and the social conflict and reaction model turned out to have low sensitivities for predicting violence. Nevertheless, all models produced acceptable results in predictions of a non-violent outcome. Copyright © 2015. Published by Elsevier Ltd.

Optical design applications for enhanced illumination performance

Science.gov (United States)

Gilray, Carl; Lewin, Ian

1995-08-01

Nonimaging optical design techniques have been applied in the illumination industry for many years. Recently however, powerful software has been developed which allows accurate simulation and optimization of illumination devices. Wide experience has been obtained in using such design techniques for practical situations. These include automotive lighting where safety is of greatest importance, commercial lighting systems designed for energy efficiency, and numerous specialized applications. This presentation will discuss the performance requirements of a variety of illumination devices. It will further cover design methodology and present a variety of examples of practical applications for enhanced system performance.

Prediction of the Long Term Cooling Performance for the 3-Pin Fuel Test Loop

Energy Technology Data Exchange (ETDEWEB)

Park, S. K.; Chi, D. Y.; Sim, B. S.; Park, K. N.; Ahn, S. H.; Lee, J. M.; Lee, C. Y.; Kim, H. R

2005-12-15

In the long term cooling phase that the emergency cooling water injection ends, the performance of the residual heat removal for the 3-pin fuel test loop has been predicted by a simplified heat transfer model. In the long term cooling phase the residual heat is 1323W for PWR fuel test mode and 1449W for CANDU fuel test mode. The each residual heat is assumed as 2% of the fission power of the test fuel used in the anticipated operational occurrence and design basis accident analyses. The each fission power used for the analyses is 105% of the rated fission power in the normal operation. In the long term cooling phase the residual heat is removed to the HANARO pool through the double pressure vessels of the in-pile test section. Saturate pooling boiling is assumed on the test fuel and condensation heat transfer is expected on the inner wall of the fuel carrier and the flow divider. Natural convection heat transfer on a heated vertical wall is also assumed on the outer wall of the outer pressure vessel. The conduction heat transfer is only considered in the gap between the double pressure vessels charged with neon gas and in the downcomer filled with coolant. The heat transfer rate between the coolant temperature of 152 .deg. C in the in-pile test section and the water temperature of 45 .deg. C in the HANARO pool is predicted as about 1666W. The 152 .deg. C is the saturate temperature of the coolant pressure predicted from the MARS code. The cooling capacity of 1666W is greater than the residual heats of 1323W and 1449W. Consequently the long term cooling performance of the 3-pin fuel test loop is sufficient for the anticipated operational occurrences and design basis accidents.

Entity versus incremental theories predict older adults' memory performance.

Science.gov (United States)

Plaks, Jason E; Chasteen, Alison L

2013-12-01

The authors examined whether older adults' implicit theories regarding the modifiability of memory in particular (Studies 1 and 3) and abilities in general (Study 2) would predict memory performance. In Study 1, individual differences in older adults' endorsement of the "entity theory" (a belief that one's ability is fixed) or "incremental theory" (a belief that one's ability is malleable) of memory were measured using a version of the Implicit Theories Measure (Dweck, 1999). Memory performance was assessed with a free-recall task. Results indicated that the higher the endorsement of the incremental theory, the better the free recall. In Study 2, older and younger adults' theories were measured using a more general version of the Implicit Theories Measure that focused on the modifiability of abilities in general. Again, for older adults, the higher the incremental endorsement, the better the free recall. Moreover, as predicted, implicit theories did not predict younger adults' memory performance. In Study 3, participants read mock news articles reporting evidence in favor of either the entity or incremental theory. Those in the incremental condition outperformed those in the entity condition on reading span and free-recall tasks. These effects were mediated by pretask worry such that, for those in the entity condition, higher worry was associated with lower performance. Taken together, these studies suggest that variation in entity versus incremental endorsement represents a key predictor of older adults' memory performance. PsycINFO Database Record (c) 2013 APA, all rights reserved.

The Role of a PMI-Prediction Model in Evaluating Forensic Entomology Experimental Design, the Importance of Covariates, and the Utility of Response Variables for Estimating Time Since Death

Directory of Open Access Journals (Sweden)

Jeffrey Wells

2017-05-01

Full Text Available The most common forensic entomological application is the estimation of some portion of the time since death, or postmortem interval (PMI. To our knowledge, a PMI estimate is almost never accompanied by an associated probability. Statistical methods are now available for calculating confidence limits for an insect-based prediction of PMI for both succession and development data. In addition to it now being possible to employ these approaches in validation experiments and casework, it is also now possible to use the criterion of prediction performance to guide training experiments, i.e., to modify carrion insect development or succession experiment design in ways likely to improve the performance of PMI predictions using the resulting data. In this paper, we provide examples, derived from our research program on calculating PMI estimate probabilities, of how training data experiment design can influence the performance of a statistical model for PMI prediction.

The design and performance of the electromagnetic calorimeters in Hall C at Jefferson Lab

International Nuclear Information System (INIS)

Tadevosyan, V; Mkrtchyan, H; Asaturyan, A; Mkrtchyan, A; Zhamkochyan, S

2012-01-01

The design and performance of the electromagnetic calorimeters in the magnetic spectrometers in Hall C at Jefferson Lab are presented. For the existing HMS and SOS spectrometers, construction information and comparisons of simulated and experimental results are presented. The design and simulated performance for a new calorimeter to be used in the new SHMS spectrometer is also presented. We have developed and constructed electromagnetic calorimeters from TF-1 type lead-glass blocks for the HMS and SOS magnetic spectrometers at JLab Hall C. The HMS/SOS calorimeters are of identical design and construction except for their total size. Blocks of dimension 10 cm × 10 cm × 70 cm are arranged in four planes and stacked 13 and 11 blocks high in the HMS and SOS respectively. The energy resolution of these calorimeters is better than 6%/√E, and pion/electron (π/e) separation of about 100:1 has been achieved in energy range 1–5 GeV. Good agreement has been observed between the experimental and GEANT4 simulated energy resolutions. The HMS/SOS calorimeters have been used nearly in all Hall C experiments, providing good energy resolution and a high pion suppression factor. No significant deterioration in their performance has been observed in the course of use since 1994. For the SHMS spectrometer, presently under construction, details on the calorimeter design and accompanying GEANT4 simulation efforts are given. A Preshower+Shower design was selected as the most cost-effective among several design choices. The preshower will consist of a layer of 28 modules with TF-1 type lead glass radiators, stacked in two columns. The shower part will consist of 224 modules with F-101 type lead glass radiators, stacked in a “fly's eye” configuration of 14 columns and 16 rows. The active area of 120 × 130 cm 2 will encompass the beam envelope at the calorimeter. The anticipated performance of the new calorimeter is simulated over the full momentum range of the SHMS, predicting

Predicting off-design range and performance of refrigeration cycle with two-stage centrifugal compressor and flash intercooler

Energy Technology Data Exchange (ETDEWEB)

Turunen-Saaresti, Teemu; Roeyttae, Pekka; Honkatukia, Juha; Backman, Jari [Lappeenranta University of Technology, Institute of Energy Technology, Laboratory of Fluid Dynamics, P.O. Box 20, 53851 Lappeenranta (Finland)

2010-09-15

A modern refrigeration process requires constant control to provide required cooling for the user. To properly and economically accommodate this need, a wide operation range of the compressor is necessary. Therefore, it is of interest to investigate the off-design operation of a cooling cycle and compressor. The refrigeration cycle equipped with a two-stage centrifugal compressor and a flash intercooler is studied. The compressor operation maps are generated with two different design codes and the operation values of the compressors are interpolated from the compressor maps in the simulation of the entire cooling cycle. Based on the previous studies of the utilised refrigeration cycle, R245fa is selected as coolant. The aim of this study is to demonstrate the control capacity of the centrifugal compressor and the performance of the cooling loop in off-design conditions. This configuration provides better and wider control over the cooling range than the traditional on-off control of displacement compressors. (author)

Hybrid ANN–PLS approach to scroll compressor thermodynamic performance prediction

International Nuclear Information System (INIS)

Tian, Z.; Gu, B.; Yang, L.; Lu, Y.

2015-01-01

In this paper, a scroll compressor thermodynamic performance prediction was carried out by applying a hybrid ANN–PLS model. Firstly, an experimental platform with second-refrigeration calorimeter was set up and steady-state scroll compressor data sets were collected from experiments. Then totally 148 data sets were introduced to train and verify the validity of the ANN–PLS model for predicting the scroll compressor parameters such as volumetric efficiency, refrigerant mass flow rate, discharge temperature and power consumption. The ANN–PLS model was determined with 5 hidden neurons and 7 latent variables through the training process. Ultimately, the ANN–PLS model showed better performance than the ANN model and the PLS model working separately. ANN–PLS predictions agree well with the experimental values with mean relative errors (MREs) in the range of 0.34–1.96%, correlation coefficients (R 2 ) in the range of 0.9703–0.9999 and very low root mean square errors (RMSEs). - Highlights: • Hybrid ANN–PLS is utilized to predict the thermodynamic performance of scroll compressor. • ANN–PLS model is determined with 5 hidden neurons and 7 latent variables. • ANN–PLS model demonstrates better performance than ANN and PLS working separately. • The values of MRE and RMSE are in the range of 0.34–1.96% and 0.9703–0.9999, respectively

Prediction of Heat Transfer Performance on Horizontal U-Shaped Heat Exchanger in Passive Safety System Using MARS

Energy Technology Data Exchange (ETDEWEB)

Jeon, Seong-Su; Hong, Soon-Joon [FNC Tech, Yongin (Korea, Republic of); Cho, Hyoung-Kyu; Park, Goon-Cherl [Seoul National University, Seoul (Korea, Republic of)

2015-10-15

The design and the safety analysis of the passive safety systems are performed mainly using the best-estimate thermal-hydraulic analysis codes such as RELAP5 and MARS. This study developed the heat transfer model package for the horizontal U-shaped HX submerged in a pool by improving the horizontal in-tube condensation model and developing the outside-tube natural convective nucleate boiling model. This paper presents the HX model package and the validation results against the passive safety system-related experimental data of PASCAL and ATLAS-PAFS. This study developed the heat transfer model package of the horizontal U-shaped HX submerged in a pool in order to obtain a reliable prediction of the HX heat removal performance of the passive safety system, especially PAFS, using MARS. From the validation results, the proposed model package provided the improved prediction of HX performance (condensation, natural convective nucleate boiling, and heat removal rate of the HX) compared to the default model in MARS.

Prehospital Acute Stroke Severity Scale to Predict Large Artery Occlusion: Design and Comparison With Other Scales.

Science.gov (United States)

Hastrup, Sidsel; Damgaard, Dorte; Johnsen, Søren Paaske; Andersen, Grethe

2016-07-01

We designed and validated a simple prehospital stroke scale to identify emergent large vessel occlusion (ELVO) in patients with acute ischemic stroke and compared the scale to other published scales for prediction of ELVO. A national historical test cohort of 3127 patients with information on intracranial vessel status (angiography) before reperfusion therapy was identified. National Institutes of Health Stroke Scale (NIHSS) items with the highest predictive value of occlusion of a large intracranial artery were identified, and the most optimal combination meeting predefined criteria to ensure usefulness in the prehospital phase was determined. The predictive performance of Prehospital Acute Stroke Severity (PASS) scale was compared with other published scales for ELVO. The PASS scale was composed of 3 NIHSS scores: level of consciousness (month/age), gaze palsy/deviation, and arm weakness. In derivation of PASS 2/3 of the test cohort was used and showed accuracy (area under the curve) of 0.76 for detecting large arterial occlusion. Optimal cut point ≥2 abnormal scores showed: sensitivity=0.66 (95% CI, 0.62-0.69), specificity=0.83 (0.81-0.85), and area under the curve=0.74 (0.72-0.76). Validation on 1/3 of the test cohort showed similar performance. Patients with a large artery occlusion on angiography with PASS ≥2 had a median NIHSS score of 17 (interquartile range=6) as opposed to PASS <2 with a median NIHSS score of 6 (interquartile range=5). The PASS scale showed equal performance although more simple when compared with other scales predicting ELVO. The PASS scale is simple and has promising accuracy for prediction of ELVO in the field. © 2016 American Heart Association, Inc.

Aqua/Aura Updated Inclination Adjust Maneuver Performance Prediction Model

Science.gov (United States)

Boone, Spencer

2017-01-01

This presentation will discuss the updated Inclination Adjust Maneuver (IAM) performance prediction model that was developed for Aqua and Aura following the 2017 IAM series. This updated model uses statistical regression methods to identify potential long-term trends in maneuver parameters, yielding improved predictions when re-planning past maneuvers. The presentation has been reviewed and approved by Eric Moyer, ESMO Deputy Project Manager.

Prediction of Tennis Performance in Junior Elite Tennis Players

Directory of Open Access Journals (Sweden)

Tamara Kramer, Barbara C.H. Huijgen, Marije T. Elferink-Gemser, Chris Visscher

2017-03-01

Full Text Available Predicting current and future tennis performance can lead to improving the development of junior tennis players. The aim of this study is to investigate whether age, maturation, or physical fitness in junior elite tennis players in U13 can explain current and future tennis performance. The value of current tennis performance for future tennis performance is also investigated. A total of 86 junior elite tennis players (boys, n = 44; girls, n = 42 U13 (aged: 12.5 ± 0.3 years, and followed to U16, took part in this study. All players were top-30 ranked on the Dutch national ranking list at U13, and top-50 at U16. Age, maturation, and physical fitness, were measured at U13. A principal component analysis was used to extract four physical components from eight tests (medicine ball throwing overhead and reverse, ball throwing, SJ, CMJas, Sprint 5 and 10 meter, and the spider test. The possible relationship of age, maturation, and the physical components; “upper body power”, “lower body power”, “speed”, and “agility” with tennis performance at U13 and U16 was analyzed. Tennis performance was measured by using the ranking position on the Dutch national ranking list at U13 and U16. Regression analyses were conducted based on correlations between variables and tennis performance for boys and girls, separately. In boys U13, positive correlations were found between upper body power and tennis performance (R2 is 25%. In girls, positive correlations between maturation and lower body power with tennis performance were found at U13. Early maturing players were associated with a better tennis performance (R2 is 15%. In girls U16, only maturation correlated with tennis performance (R2 is 13%; later-maturing girls at U13 had better tennis performances at U16. Measuring junior elite tennis players at U13 is important for monitoring their development. These measurements did not predict future tennis performance of junior elite tennis players three

Time-predictable Stack Caching

DEFF Research Database (Denmark)

Abbaspourseyedi, Sahar

completely. Thus, in systems with hard deadlines the worst-case execution time (WCET) of the real-time software running on them needs to be bounded. Modern architectures use features such as pipelining and caches for improving the average performance. These features, however, make the WCET analysis more...... addresses, provides an opportunity to predict and tighten the WCET of accesses to data in caches. In this thesis, we introduce the time-predictable stack cache design and implementation within a time-predictable processor. We introduce several optimizations to our design for tightening the WCET while...... keeping the timepredictability of the design intact. Moreover, we provide a solution for reducing the cost of context switching in a system using the stack cache. In design of these caches, we use custom hardware and compiler support for delivering time-predictable stack data accesses. Furthermore...

Design, construction, and performance of superconducting magnet support posts for the Large Hadron Collider

International Nuclear Information System (INIS)

Blin, M.; Danielsson, H.; Evans, B.; Mathieu, M.

1994-01-01

Different support posts for the Large Hadron Collider (LHC) prototype superconducting magnets have been designed and manufactured. They have been evaluated both mechanically and thermally. The posts are made of a tubular section in composite materials, i.e. glass- or carbon-fibre and epoxy resin, with glued metallic heat intercepts and connections. Mechanical tests have been carried out with both radial and axial loads, before and after cooldown to working temperature. The design considerations and future developments concerning dimensions and other materials are also discussed in this paper. Thermal performance has been evaluated at 1.8 K, 5 K and 80 K in a precision heat leak measuring bench. The measurements have been carried out using calibrated thermal conductances (open-quotes heatmetersclose quotes) and boil-off methods. The measured performances of the posts have been compared with analytical predictions

Burst muscle performance predicts the speed, acceleration, and turning performance of Anna’s hummingbirds

Science.gov (United States)

Segre, Paolo S; Dakin, Roslyn; Zordan, Victor B; Dickinson, Michael H; Straw, Andrew D; Altshuler, Douglas L

2015-01-01

Despite recent advances in the study of animal flight, the biomechanical determinants of maneuverability are poorly understood. It is thought that maneuverability may be influenced by intrinsic body mass and wing morphology, and by physiological muscle capacity, but this hypothesis has not yet been evaluated because it requires tracking a large number of free flight maneuvers from known individuals. We used an automated tracking system to record flight sequences from 20 Anna's hummingbirds flying solo and in competition in a large chamber. We found that burst muscle capacity predicted most performance metrics. Hummingbirds with higher burst capacity flew with faster velocities, accelerations, and rotations, and they used more demanding complex turns. In contrast, body mass did not predict variation in maneuvering performance, and wing morphology predicted only the use of arcing turns and high centripetal accelerations. Collectively, our results indicate that burst muscle capacity is a key predictor of maneuverability. DOI: http://dx.doi.org/10.7554/eLife.11159.001 PMID:26583753

Seismic design of circular-section concrete-lined underground openings: Preclosure performance considerations for the Yucca Mountain Site

International Nuclear Information System (INIS)

Richardson, A.M.; Blejwas, T.E.

1992-01-01

Yucca Mountain, the potential site of a repository for high-level radioactive waste, is situated in a region of natural and man-made seismicity. Underground openings excavated at this site must be designed for worker safety in the seismic environment anticipated for the preclosure period. This includes accesses developed for site characterization regardless of the ultimate outcome of the repository siting process. Experience with both civil and mining structures has shown that underground openings are much more resistant to seismic effects than surface structures, and that even severe dynamic strains can usually be accommodated with proper design. This paper discusses the design and performance of lined openings in the seismic environment of the potential site. The types and ranges of possible ground motions (seismic loads) are briefly discussed. Relevant historical records of underground opening performance during seismic loading are reviewed. Simple analytical methods of predicting liner performance under combined in situ, thermal, and seismic loading are presented, and results of calculations are discussed in the context of realistic performance requirements for concrete-lined openings for the preclosure period. Design features that will enhance liner stability and mitigate the impact of the potential seismic load are reviewed. The paper is limited to preclosure performance concerns involving worker safety because present decommissioning plans specify maintaining the option for liner removal at seal locations, thus decoupling liner design from repository postclosure performance issues

Correlation of Amine Swingbed On-Orbit CO2 Performance with a Hardware Independent Predictive Model

Science.gov (United States)

Papale, William; Sweterlitsch, Jeffery

2015-01-01

The Amine Swingbed Payload is an experimental system deployed on the International Space Station (ISS) that includes a two-bed, vacuum regenerated, amine-based carbon dioxide (CO2) removal subsystem as the principal item under investigation. The aminebased subsystem, also described previously in various publications as CAMRAS 3, was originally designed, fabricated and tested by Hamilton Sundstrand Space Systems International, Inc. (HSSSI) and delivered to NASA in November 2008. The CAMRAS 3 unit was subsequently designed into a flight payload experiment in 2010 and 2011, with flight test integration activities accomplished on-orbit between January 2012 and March 2013. Payload activation was accomplished in May 2013 followed by a 1000 hour experimental period. The experimental nature of the Payload and the interaction with the dynamic ISS environment present unique scientific and engineering challenges, in particular to the verification and validation of the expected Payload CO2 removal performance. A modeling and simulation approach that incorporates principles of chemical reaction engineering has been developed for the amine-based system to predict the dynamic cabin CO2 partial pressure with given inputs of sorbent bed size, process air flow, operating temperature, half-cycle time, CO2 generation rate, cabin volume and the magnitude of vacuum available. Simulation runs using the model to predict ambient CO2 concentrations show good correlation to on-orbit performance measurements and ISS dynamic concentrations for the assumed operating conditions. The dynamic predictive modelling could benefit operational planning to help ensure ISS CO2 concentrations are maintained below prescribed limits and for the Orion vehicle to simulate various operating conditions, scenarios and transients.

LEARNING STYLES AND STUDENTS’ PERFORMANCE IN DESIGN PROBLEM SOLVING

Directory of Open Access Journals (Sweden)

Elçin Tezel

2010-07-01

Full Text Available Design curricula and all core design studio courses are prepared for performance attainment by giving theoretical and professional training. However students’ performance may be affected by both the constraints set on a design problem, and their learning styles. This study explores the performance of interior architectural students in relation to their learning styles (as proposed by Kolb’s Experiential Learning Theory, and different types of constraints set on design problems. Design performance, measured as conceptual development, form and spatial configuration, structural innovation and ergonomics, and craftsmanship, was found to change throughout the two bipolar continuum of the learning cycle with regard to two design conditions characterized by different types of constraint use.

Predicting law enforcement officer job performance with the Personality Assessment Inventory.

Science.gov (United States)

Lowmaster, Sara E; Morey, Leslie C

2012-01-01

This study examined the descriptive and predictive characteristics of the Personality Assessment Inventory (PAI; Morey, 1991) in a sample of 85 law enforcement officer candidates. Descriptive results indicate that mean PAI full-scale and subscale scores are consistently lower than normative community sample scores, with some exceptions noted typically associated with defensive responding. Predictive validity was examined by relating PAI full-scale and subscale scores to supervisor ratings in the areas of job performance, integrity problems, and abuse of disability status. Modest correlations were observed for all domains; however, predictive validity was moderated by defensive response style, with greater predictive validity observed among less defensive responders. These results suggest that the PAI's full scales and subscales are able to predict law enforcement officers' performance, but their utility is appreciably improved when taken in the context of indicators of defensive responding.

Search performance is better predicted by tileability than presence of a unique basic feature

Science.gov (United States)

Chang, Honghua; Rosenholtz, Ruth

2016-01-01

Traditional models of visual search such as feature integration theory (FIT; Treisman & Gelade, 1980), have suggested that a key factor determining task difficulty consists of whether or not the search target contains a “basic feature” not found in the other display items (distractors). Here we discriminate between such traditional models and our recent texture tiling model (TTM) of search (Rosenholtz, Huang, Raj, Balas, & Ilie, 2012b), by designing new experiments that directly pit these models against each other. Doing so is nontrivial, for two reasons. First, the visual representation in TTM is fully specified, and makes clear testable predictions, but its complexity makes getting intuitions difficult. Here we elucidate a rule of thumb for TTM, which enables us to easily design new and interesting search experiments. FIT, on the other hand, is somewhat ill-defined and hard to pin down. To get around this, rather than designing totally new search experiments, we start with five classic experiments that FIT already claims to explain: T among Ls, 2 among 5s, Q among Os, O among Qs, and an orientation/luminance-contrast conjunction search. We find that fairly subtle changes in these search tasks lead to significant changes in performance, in a direction predicted by TTM, providing definitive evidence in favor of the texture tiling model as opposed to traditional views of search. PMID:27548090

Design and performance of coded aperture optical elements for the CESR-TA x-ray beam size monitor

Energy Technology Data Exchange (ETDEWEB)

Alexander, J.P.; Chatterjee, A.; Conolly, C.; Edwards, E.; Ehrlichman, M.P. [Cornell University, Ithaca, NY 14853 (United States); Flanagan, J.W. [High Energy Accelerator Research Organization (KEK), Tsukuba (Japan); Department of Accelerator Science, Graduate University for Advanced Studies (SOKENDAI), Tsukuba (Japan); Fontes, E. [Cornell University, Ithaca, NY 14853 (United States); Heltsley, B.K., E-mail: bkh2@cornell.edu [Cornell University, Ithaca, NY 14853 (United States); Lyndaker, A.; Peterson, D.P.; Rider, N.T.; Rubin, D.L.; Seeley, R.; Shanks, J. [Cornell University, Ithaca, NY 14853 (United States)

2014-12-11

We describe the design and performance of optical elements for an x-ray beam size monitor (xBSM), a device measuring e{sup +} and e{sup −} beam sizes in the CESR-TA storage ring. The device can measure vertical beam sizes of 10–100μm on a turn-by-turn, bunch-by-bunch basis at e{sup ±} beam energies of ∼2–5GeV. x-rays produced by a hard-bend magnet pass through a single- or multiple-slit (coded aperture) optical element onto a detector. The coded aperture slit pattern and thickness of masking material forming that pattern can both be tuned for optimal resolving power. We describe several such optical elements and show how well predictions of simple models track measured performances. - Highlights: • We characterize optical element performance of an e{sup ±} x-ray beam size monitor. • We standardize beam size resolving power measurements to reference conditions. • Standardized resolving power measurements compare favorably to model predictions. • Key model features include simulation of photon-counting statistics and image fitting. • Results validate a coded aperture design optimized for the x-ray spectrum encountered.

Historical Trust Levels Predict Current Welfare State Design

DEFF Research Database (Denmark)

Bergh, Andreas; Bjørnskov, Christian

Using cross-sectional data for 76 countries, we apply instrumental variable techniques based on pronoun drop, temperature and monarchies to demonstrate that historical trust levels predict several indicators of current welfare state design, including universalism and high levels of regulatory...... freedom. We argue that high levels of trust and trustworthiness are necessary, but not sufficient, conditions for societies to develop successful universal welfare states that would otherwise be highly vulnerable to free riding and fraudulent behavior. Our results do not exclude positive feedback from...... welfare state universalism to individual trust, although we claim that the important causal link runs from historically trust levels to current welfare state design....

Performance Analysis and Design Strategy for a Second-Order, Fixed-Gain, Position-Velocity-Measured (α-β-η-θ Tracking Filter

Directory of Open Access Journals (Sweden)

Kenshi Saho

2017-07-01

Full Text Available We present a strategy for designing an α - β - η - θ filter, a fixed-gain moving-object tracking filter using position and velocity measurements. First, performance indices and stability conditions for the filter are analytically derived. Then, an optimal gain design strategy using these results is proposed and its relationship to the position-velocity-measured (PVM Kalman filter is shown. Numerical analyses demonstrate the effectiveness of the proposed strategy, as well as a performance improvement over the traditional position-only-measured α - β filter. Moreover, we apply an α - β - η - θ filter designed using this strategy to ultra-wideband Doppler radar tracking in numerical simulations. We verify that the proposed strategy can easily design the gains for an α - β - η - θ filter based on the performance of the ultra-wideband Doppler radar and a rough approximation of the target’s acceleration. Moreover, its effectiveness in predicting the steady state performance in designing the position-velocity-measured Kalman filter is also demonstrated.

REVIEW OF MECHANISTIC UNDERSTANDING AND MODELING AND UNCERTAINTY ANALYSIS METHODS FOR PREDICTING CEMENTITIOUS BARRIER PERFORMANCE

Energy Technology Data Exchange (ETDEWEB)

Langton, C.; Kosson, D.

2009-11-30

Cementitious barriers for nuclear applications are one of the primary controls for preventing or limiting radionuclide release into the environment. At the present time, performance and risk assessments do not fully incorporate the effectiveness of engineered barriers because the processes that influence performance are coupled and complicated. Better understanding the behavior of cementitious barriers is necessary to evaluate and improve the design of materials and structures used for radioactive waste containment, life extension of current nuclear facilities, and design of future nuclear facilities, including those needed for nuclear fuel storage and processing, nuclear power production and waste management. The focus of the Cementitious Barriers Partnership (CBP) literature review is to document the current level of knowledge with respect to: (1) mechanisms and processes that directly influence the performance of cementitious materials (2) methodologies for modeling the performance of these mechanisms and processes and (3) approaches to addressing and quantifying uncertainties associated with performance predictions. This will serve as an important reference document for the professional community responsible for the design and performance assessment of cementitious materials in nuclear applications. This review also provides a multi-disciplinary foundation for identification, research, development and demonstration of improvements in conceptual understanding, measurements and performance modeling that would be lead to significant reductions in the uncertainties and improved confidence in the estimating the long-term performance of cementitious materials in nuclear applications. This report identifies: (1) technology gaps that may be filled by the CBP project and also (2) information and computational methods that are in currently being applied in related fields but have not yet been incorporated into performance assessments of cementitious barriers. The various

Review Of Mechanistic Understanding And Modeling And Uncertainty Analysis Methods For Predicting Cementitious Barrier Performance

International Nuclear Information System (INIS)

Langton, C.; Kosson, D.

2009-01-01

Cementitious barriers for nuclear applications are one of the primary controls for preventing or limiting radionuclide release into the environment. At the present time, performance and risk assessments do not fully incorporate the effectiveness of engineered barriers because the processes that influence performance are coupled and complicated. Better understanding the behavior of cementitious barriers is necessary to evaluate and improve the design of materials and structures used for radioactive waste containment, life extension of current nuclear facilities, and design of future nuclear facilities, including those needed for nuclear fuel storage and processing, nuclear power production and waste management. The focus of the Cementitious Barriers Partnership (CBP) literature review is to document the current level of knowledge with respect to: (1) mechanisms and processes that directly influence the performance of cementitious materials (2) methodologies for modeling the performance of these mechanisms and processes and (3) approaches to addressing and quantifying uncertainties associated with performance predictions. This will serve as an important reference document for the professional community responsible for the design and performance assessment of cementitious materials in nuclear applications. This review also provides a multi-disciplinary foundation for identification, research, development and demonstration of improvements in conceptual understanding, measurements and performance modeling that would be lead to significant reductions in the uncertainties and improved confidence in the estimating the long-term performance of cementitious materials in nuclear applications. This report identifies: (1) technology gaps that may be filled by the CBP project and also (2) information and computational methods that are in currently being applied in related fields but have not yet been incorporated into performance assessments of cementitious barriers. The various

Architectural design and energy performance; Conception architecturale et performance energetique

Energy Technology Data Exchange (ETDEWEB)

Beaud, Ph. [Agence de l' Environnement et de la Maitrise de l' Energie, (ADEME), 06 - Valbonne (France); Pouget, A. [Bureau Etude Thermique, 75 - Paris (France); Sesolis, B. [TRIBU, 75 - Paris (France)] [and others

2000-07-01

This day was organized around the energy performance of the architecture in three parts. A first time dealt with the design of new buildings and private houses. Simulation tools for the energy optimization and practice of design are discussed. The second part was devoted to the new 2000 regulation with an open discussion on the regulatory costs. The last part forecasted the evolution until 2015 taking into account the french program of fight against the greenhouse effect, the limitation of the air conditioning consumption and the definition of a quality label concerning the energy performances. (A.L.B.)

Performance reliability prediction for thermal aging based on kalman filtering

International Nuclear Information System (INIS)

Ren Shuhong; Wen Zhenhua; Xue Fei; Zhao Wensheng

2015-01-01

The performance reliability of the nuclear power plant main pipeline that failed due to thermal aging was studied by the performance degradation theory. Firstly, through the data obtained from the accelerated thermal aging experiments, the degradation process of the impact strength and fracture toughness of austenitic stainless steel material of the main pipeline was analyzed. The time-varying performance degradation model based on the state space method was built, and the performance trends were predicted by using Kalman filtering. Then, the multi-parameter and real-time performance reliability prediction model for the main pipeline thermal aging was developed by considering the correlation between the impact properties and fracture toughness, and by using the stochastic process theory. Thus, the thermal aging performance reliability and reliability life of the main pipeline with multi-parameter were obtained, which provides the scientific basis for the optimization management of the aging maintenance decision making for nuclear power plant main pipelines. (authors)

The prediction of swimming performance in competition from behavioral information.

Science.gov (United States)

Rushall, B S; Leet, D

1979-06-01

The swimming performances of the Canadian Team at the 1976 Olympic Games were categorized as being improved or worse than previous best times in the events contested. The two groups had been previously assessed on the Psychological Inventories for Competitive Swimmers. A stepwise multiple-discriminant analysis of the inventory responses revealed that 13 test questions produced a perfect discrimination of group membership. The resultant discriminant functions for predicting performance classification were applied to the test responses of 157 swimmers at the 1977 Canadian Winter National Swimming Championships. Using the same performance classification criteria the accuracy of prediction was not better than chance in three of four sex by performance classifications. This yielded a failure to locate a set of behavioral factors which determine swimming performance improvements in elite competitive circumstances. The possibility of sets of factors which do not discriminate between performances in similar environments or between similar groups of swimmers was raised.

Predictive control of irrigation canals – robust design and real-time implementation

NARCIS (Netherlands)

Aguilar, José V.; Langarita, Pedro; Rodellar, José; Linares, Lorenzo; Horváth, K.

2016-01-01

Predictive control is one of the most commonly used control methods in a variety of application areas, including hydraulic processes such as water distribution canals for irrigation. This article presents the design and application of predictive control for the water discharge entering into an

Analysis of the Performance of a Laser Scanner for Predictive Automotive Applications

Science.gov (United States)

Zeisler, J.; Maas, H.-G.

2015-08-01

In this paper we evaluate the use of a laser scanner for future advanced driver assistance systems. We focus on the important task of predicting the target vehicle for longitudinal ego vehicle control. Our motivation is to decrease the reaction time of existing systems during cut-in maneuvers of other traffic participants. A state-of-the-art laser scanner, the Ibeo Scala B2 R , is presented, providing its sensing characteristics and the subsequent high level object data output. We evaluate the performance of the scanner towards object tracking with the help of a GPS real time kinematics system on a test track. Two designed scenarios show phases with constant distance and velocity as well as dynamic motion of the vehicles. We provide the results for the error in position and velocity of the scanner and furthermore, review our algorithm for target vehicle prediction. Finally we show the potential of the laser scanner with the estimated error, that leads to a decrease of up to 40% in reaction time with best conditions.

An Integrated Lumped Parameter-CFD approach for off-design ejector performance evaluation

International Nuclear Information System (INIS)

Besagni, Giorgio; Mereu, Riccardo; Chiesa, Paolo; Inzoli, Fabio

2015-01-01

Highlights: • We validate a CFD approach for a convergent nozzle ejector using global and local measurement. • We evaluate seven RANS turbulence models for convergent nozzle ejector. • We introduce a lumped parameter model for on-design and off-design ejector performance evaluation. • We analyze the relationship between local flow behavior and lumped parameters of the model. • We discuss how to improve predicting capabilities of the model by variable parameters calibrated on CFD simulations. - Abstract: This paper presents an Integrated Lumped Parameter Model-Computational Fluid-Dynamics approach for off-design ejector performance evaluation. The purpose of this approach is to evaluate the entrainment ratio, for a fixed geometry, in both on-design and off-design operating conditions. The proposed model is based on a Lumped Parameter Model (LPM) with variable ejector component efficiencies provided by CFD simulations. The CFD results are used for developing maps for ejector component efficiencies in a broad range of operating conditions. The ejector component efficiency maps couple the CFD and the LPM techniques for building an Integrated LPM-CFD approach. The proposed approach is demonstrated for a convergent nozzle ejector and the paper is structured in four parts. At first, the CFD approach is validated by global and local data and seven Reynolds Averaged Navier Stokes (RANS) turbulence models are compared: the k–ω SST showed good performance and was selected for the rest of the analysis. At second, a Lumped Parameter Model (LPM) for subsonic ejector is developed and the ejector component efficiencies have been defined. At third, the CFD approach is used to investigate the flow field, to analyze its influence on ejector component efficiencies and to propose efficiency correlations and maps linking ejector component efficiencies and local flow quantities. In the last part, the efficiency maps are embedded into the lumped parameter model, thus creating

Essays on predictability of emerging markets growth and financial performance

OpenAIRE

Banegas, Maria Ayelen

2011-01-01

This dissertation seeks to better understand the underlying factors driving financial performance and economic activity in international markets. The first chapter "Predictability of Growth in Emerging Markets: Information in Financial Aggregates" tests for predictability of output growth in a panel of twenty-two emerging market economies. I use pooled panel data methods that control for endogeneity and persistence in the predictor variables to test the predictive power of a large set of fina...

The joint effects of personality and workplace social exchange relationships in predicting task performance and citizenship performance.

Science.gov (United States)

Kamdar, Dishan; Van Dyne, Linn

2007-09-01

This field study examines the joint effects of social exchange relationships at work (leader-member exchange and team-member exchange) and employee personality (conscientiousness and agreeableness) in predicting task performance and citizenship performance. Consistent with trait activation theory, matched data on 230 employees, their coworkers, and their supervisors demonstrated interactions in which high quality social exchange relationships weakened the positive relationships between personality and performance. Results demonstrate the benefits of consonant predictions in which predictors and outcomes are matched on the basis of specific targets. We discuss theoretical and practical implications. (c) 2007 APA.

Aerodynamic Optimization Design of a Multistage Centrifugal Steam Turbine and Its Off-Design Performance Analysis

Directory of Open Access Journals (Sweden)

Hui Li

2017-01-01

Full Text Available Centrifugal turbine which has less land occupation, simple structure, and high aerodynamic efficiency is suitable to be used as small to medium size steam turbines or waste heat recovery plant. In this paper, one-dimensional design of a multistage centrifugal steam turbine was performed by using in-house one-dimensional aerodynamic design program. In addition, three-dimensional numerical simulation was also performed in order to analyze design and off-design aerodynamic performance of the proposed centrifugal steam turbine. The results exhibit reasonable flow field and smooth streamline; the aerodynamic performance of the designed turbine meets our initial expectations. These results indicate that the one-dimensional aerodynamic design program is reliable and effective. The off-design aerodynamic performance of centrifugal steam turbine was analyzed, and the results show that the mass flow increases with the decrease of the pressure ratio at a constant speed, until the critical mass flow is reached. The efficiency curve with the pressure ratio has an optimum efficiency point. And the pressure ratio of the optimum efficiency agrees well with that of the one-dimensional design. The shaft power decreases as the pressure ratio increases at a constant speed. Overall, the centrifugal turbine has a wide range and good off-design aerodynamic performance.

STUDENT ACADEMIC PERFORMANCE PREDICTION USING SUPPORT VECTOR MACHINE

OpenAIRE

S.A. Oloruntoba1 ,J.L.Akinode2

2017-01-01

This paper investigates the relationship between students' preadmission academic profile and final academic performance. Data Sample of students in one of the Federal Polytechnic in south West part of Nigeria was used. The preadmission academic profile used for this study is the 'O' level grades(terminal high school results).The academic performance is defined using student's Grade Point Average(GPA). This research focused on using data mining technique to develop a model for predicting stude...

Computational Human Performance Modeling For Alarm System Design

Energy Technology Data Exchange (ETDEWEB)

Jacques Hugo

2012-07-01

The introduction of new technologies like adaptive automation systems and advanced alarms processing and presentation techniques in nuclear power plants is already having an impact on the safety and effectiveness of plant operations and also the role of the control room operator. This impact is expected to escalate dramatically as more and more nuclear power utilities embark on upgrade projects in order to extend the lifetime of their plants. One of the most visible impacts in control rooms will be the need to replace aging alarm systems. Because most of these alarm systems use obsolete technologies, the methods, techniques and tools that were used to design the previous generation of alarm system designs are no longer effective and need to be updated. The same applies to the need to analyze and redefine operators’ alarm handling tasks. In the past, methods for analyzing human tasks and workload have relied on crude, paper-based methods that often lacked traceability. New approaches are needed to allow analysts to model and represent the new concepts of alarm operation and human-system interaction. State-of-the-art task simulation tools are now available that offer a cost-effective and efficient method for examining the effect of operator performance in different conditions and operational scenarios. A discrete event simulation system was used by human factors researchers at the Idaho National Laboratory to develop a generic alarm handling model to examine the effect of operator performance with simulated modern alarm system. It allowed analysts to evaluate alarm generation patterns as well as critical task times and human workload predicted by the system.

Prediction of Rowing Ergometer Performance from Functional Anaerobic Power, Strength and Anthropometric Components

Directory of Open Access Journals (Sweden)

Akça Firat

2014-07-01

Full Text Available The aim of this research was to develop different regression models to predict 2000 m rowing ergometer performance with the use of anthropometric, anaerobic and strength variables and to determine how precisely the prediction models constituted by different variables predict performance, when conducted together in the same equation or individually. 38 male collegiate rowers (20.17 ± 1.22 years participated in this study. Anthropometric, strength, 2000 m maximal rowing ergometer and rowing anaerobic power tests were applied. Multiple linear regression procedures were employed in SPSS 16 to constitute five different regression formulas using a different group of variables. The reliability of the regression models was expressed by R2 and the standard error of estimate (SEE. Relationships of all parameters with performance were investigated through Pearson correlation coefficients. The prediction model using a combination of anaerobic, strength and anthropometric variables was found to be the most reliable equation to predict 2000 m rowing ergometer performance (R2 = 0.92, SEE= 3.11 s. Besides, the equation that used rowing anaerobic and strength test results also provided a reliable prediction (R2 = 0.85, SEE= 4.27 s. As a conclusion, it seems clear that physiological determinants which are affected by anaerobic energy pathways should also get involved in the processes and models used for performance prediction and talent identification in rowing.

2B-Alert Web: An Open-Access Tool for Predicting the Effects of Sleep/Wake Schedules and Caffeine Consumption on Neurobehavioral Performance.

Science.gov (United States)

Reifman, Jaques; Kumar, Kamal; Wesensten, Nancy J; Tountas, Nikolaos A; Balkin, Thomas J; Ramakrishnan, Sridhar

2016-12-01

Computational tools that predict the effects of daily sleep/wake amounts on neurobehavioral performance are critical components of fatigue management systems, allowing for the identification of periods during which individuals are at increased risk for performance errors. However, none of the existing computational tools is publicly available, and the commercially available tools do not account for the beneficial effects of caffeine on performance, limiting their practical utility. Here, we introduce 2B-Alert Web, an open-access tool for predicting neurobehavioral performance, which accounts for the effects of sleep/wake schedules, time of day, and caffeine consumption, while incorporating the latest scientific findings in sleep restriction, sleep extension, and recovery sleep. We combined our validated Unified Model of Performance and our validated caffeine model to form a single, integrated modeling framework instantiated as a Web-enabled tool. 2B-Alert Web allows users to input daily sleep/wake schedules and caffeine consumption (dosage and time) to obtain group-average predictions of neurobehavioral performance based on psychomotor vigilance tasks. 2B-Alert Web is accessible at: https://2b-alert-web.bhsai.org. The 2B-Alert Web tool allows users to obtain predictions for mean response time, mean reciprocal response time, and number of lapses. The graphing tool allows for simultaneous display of up to seven different sleep/wake and caffeine schedules. The schedules and corresponding predicted outputs can be saved as a Microsoft Excel file; the corresponding plots can be saved as an image file. The schedules and predictions are erased when the user logs off, thereby maintaining privacy and confidentiality. The publicly accessible 2B-Alert Web tool is available for operators, schedulers, and neurobehavioral scientists as well as the general public to determine the impact of any given sleep/wake schedule, caffeine consumption, and time of day on performance of a

Passive Solar Construction--Design and Performance.

Science.gov (United States)

Conservation and Renewable Energy Inquiry and Referral Service (DOE), Silver Spring, MD.

Presented is a list of books and reports intended to serve as technical sources of information for the building professional interested in energy conservation. These publications are grouped under these headings: (1) energy-conserving building design; (2) passive systems/design; (3) passive systems/performance; and (4) proceedings (of the American…

Loss model for off-design performance analysis of radial turbines with pivoting-vane, variable-area stators

Science.gov (United States)

Meitner, P. L.; Glassman, A. J.

1980-01-01

An off-design performance loss model for a radial turbine with pivoting, variable-area stators is developed through a combination of analytical modeling and experimental data analysis. A viscous loss model is used for the variation in stator loss with setting angle, and stator vane end-clearance leakage effects are predicted by a clearance flow model. The variation of rotor loss coefficient with stator setting angle is obtained by means of an analytical matching of experimental data for a rotor that was tested with six stators, having throat areas from 20 to 144% of the design area. An incidence loss model is selected to obtain best agreement with experimental data. The stator vane end-clearance leakage model predicts increasing mass flow and decreasing efficiency as a result of end-clearances, with changes becoming significantly larger with decreasing stator area.

Mastery and Performance Goals Predict Epistemic and Relational Conflict Regulation

Science.gov (United States)

Darnon, Celine; Muller, Dominique; Schrager, Sheree M.; Pannuzzo, Nelly; Butera, Fabrizio

2006-01-01

The present research examines whether mastery and performance goals predict different ways of reacting to a sociocognitive conflict with another person over materials to be learned, an issue not yet addressed by the achievement goal literature. Results from 2 studies showed that mastery goals predicted epistemic conflict regulation (a conflict…

Design and performance of the helically coiled boilers of two AGR power stations in the United Kingdom

International Nuclear Information System (INIS)

El-Nagdy, M.; Papa, A.D.

1988-01-01

The Hartlepool and Heysham-I AGR stations have been commissioned and operating since 1983. The main features, of the design of the helical once-through boilers raising the steam for power generation, are outlined. The modifications to the feed inlet flow ferrules, necessary to improve the boiler performance and optimize the power output, have been described. Comparisons between the thermal and hydrodynamic performance of the boilers before and following these alterations are given. The improvements in the computer code predictions of the plant performance have also been presented. (author)

Chapter 6 – Computer-Aided Molecular Design and Property Prediction

DEFF Research Database (Denmark)

Gani, Rafiqul; Zhang, L.; Kalakul, Sawitree

2017-01-01

for the initial stages of the design/development process. Therefore, computer-aided molecular design and property prediction techniques are two topics that play important roles in chemical product design, analysis, and application. In this chapter, an overview of the concepts, methods, and tools related......Today's society needs many chemical-based products for its survival, nutrition, health, transportation, agriculture, and the functioning of processes. Chemical-based products have to be designed/developed in order to meet these needs, while at the same time, they must be innovative and sustainable...... to these two topics are given. In addition, a generic computer-aided framework for the design of molecules, mixtures, and blends is presented. The application of the framework is highlighted for molecular products through two case studies involving the design of refrigerants and surfactants....

Predicting Performance in Higher Education Using Proximal Predictors

NARCIS (Netherlands)

Niessen, A Susan M; Meijer, Rob R; Tendeiro, Jorge N

2016-01-01

We studied the validity of two methods for predicting academic performance and student-program fit that were proximal to important study criteria. Applicants to an undergraduate psychology program participated in a selection procedure containing a trial-studying test based on a work sample approach,

Design of a Hydro-Turbine Blade for Acoustic and Performance Validation Studies

Science.gov (United States)

Johnson, E.; Barone, M.

2011-12-01

To meet the growing, global energy demands governments and industry have recently begun to focus on marine hydrokinetic (MHK) devices as an additional form of power generation. Water turbines have become a popular design choice since they are able to leverage experience from the decades-old wind industry in the hope of decreasing time-to-market. However, the difference in environments poses challenges that need to be addressed. In particular, little research has addressed the acoustic effects of common aerofoils in a marine setting. This has both a potential impact on marine life and may cause early fatigue by exciting new structural modes. An initial blade design is presented, which has been used to begin characterization of any structural and acoustic issues that may arise from a direct one-to-one swap of wind technologies into MHK devices. The blade was optimized for performance using blade-element momentum theory while requiring that it not exceed the allowable stress under a specified extreme operating design condition. This limited the maximum power generated, while ensuring a realizable blade. A stress analysis within ANSYS was performed to validate the structural integrity of the design. Additionally, predictions of the radiated noise from the MHK rotor will be made using boundary element modeling based on flow results from ANSYS CFX, a computational fluid dynamics (CFD) code. The FEA and CFD results demonstrate good comparison to the expected design. Determining a range for the anticipated noise produced from a MHK turbine provides a look at the environmental impact these devices will have. Future efforts will focus on the design constraints noise generation places on MHK devices.

Predicting BCI subject performance using probabilistic spatio-temporal filters.

Directory of Open Access Journals (Sweden)

Heung-Il Suk

Full Text Available Recently, spatio-temporal filtering to enhance decoding for Brain-Computer-Interfacing (BCI has become increasingly popular. In this work, we discuss a novel, fully Bayesian-and thereby probabilistic-framework, called Bayesian Spatio-Spectral Filter Optimization (BSSFO and apply it to a large data set of 80 non-invasive EEG-based BCI experiments. Across the full frequency range, the BSSFO framework allows to analyze which spatio-spectral parameters are common and which ones differ across the subject population. As expected, large variability of brain rhythms is observed between subjects. We have clustered subjects according to similarities in their corresponding spectral characteristics from the BSSFO model, which is found to reflect their BCI performances well. In BCI, a considerable percentage of subjects is unable to use a BCI for communication, due to their missing ability to modulate their brain rhythms-a phenomenon sometimes denoted as BCI-illiteracy or inability. Predicting individual subjects' performance preceding the actual, time-consuming BCI-experiment enhances the usage of BCIs, e.g., by detecting users with BCI inability. This work additionally contributes by using the novel BSSFO method to predict the BCI-performance using only 2 minutes and 3 channels of resting-state EEG data recorded before the actual BCI-experiment. Specifically, by grouping the individual frequency characteristics we have nicely classified them into the subject 'prototypes' (like μ - or β -rhythm type subjects or users without ability to communicate with a BCI, and then by further building a linear regression model based on the grouping we could predict subjects' performance with the maximum correlation coefficient of 0.581 with the performance later seen in the actual BCI session.

Genome-Wide Polygenic Scores Predict Reading Performance Throughout the School Years.

Science.gov (United States)

Selzam, Saskia; Dale, Philip S; Wagner, Richard K; DeFries, John C; Cederlöf, Martin; O'Reilly, Paul F; Krapohl, Eva; Plomin, Robert

2017-07-04

It is now possible to create individual-specific genetic scores, called genome-wide polygenic scores (GPS). We used a GPS for years of education ( EduYears ) to predict reading performance assessed at UK National Curriculum Key Stages 1 (age 7), 2 (age 12) and 3 (age 14) and on reading tests administered at ages 7 and 12 in a UK sample of 5,825 unrelated individuals. EduYears GPS accounts for up to 5% of the variance in reading performance at age 14. GPS predictions remained significant after accounting for general cognitive ability and family socioeconomic status. Reading performance of children in the lowest and highest 12.5% of the EduYears GPS distribution differed by a mean growth in reading ability of approximately two school years. It seems certain that polygenic scores will be used to predict strengths and weaknesses in education.

Aerodynamic Optimization Design of a Multistage Centrifugal Steam Turbine and Its Off-Design Performance Analysis

OpenAIRE

Hui Li; Dian-Gui Huang

2017-01-01

Centrifugal turbine which has less land occupation, simple structure, and high aerodynamic efficiency is suitable to be used as small to medium size steam turbines or waste heat recovery plant. In this paper, one-dimensional design of a multistage centrifugal steam turbine was performed by using in-house one-dimensional aerodynamic design program. In addition, three-dimensional numerical simulation was also performed in order to analyze design and off-design aerodynamic performance of the pro...

Research Design and the Predictive Power of Measures of Self-Efficacy

Science.gov (United States)

Moriarty, Beverley

2014-01-01

The purpose of this enquiry was to examine how research design impacts on the predictive power of measures of self-efficacy. Three cautions for designing research into self-efficacy drawn from the seminal work of Albert Bandura (1986) and a further caution proposed by the current author together form the analytical framework for this enquiry. For…

Artificial neural network model for prediction of safety performance indicators goals in nuclear plants

Energy Technology Data Exchange (ETDEWEB)

Souto, Kelling C.; Nunes, Wallace W. [Instituto Federal de Educacao, Ciencia e Tecnologia do Rio de Janeiro, Nilopolis, RJ (Brazil). Lab. de Aplicacoes Computacionais; Machado, Marcelo D., E-mail: dornemd@eletronuclear.gov.b [ELETROBRAS Termonuclear S.A. (ELETRONUCLEAR), Rio de Janeiro, RJ (Brazil). Gerencia de Combustivel Nuclear - GCN.T

2011-07-01

Safety performance indicators have been developed to provide a quantitative indication of the performance and safety in various industry sectors. These indexes can provide assess to aspects ranging from production, design, and human performance up to management issues in accordance with policy, objectives and goals of the company. The use of safety performance indicators in nuclear power plants around the world is a reality. However, it is necessary to periodically set goal values. Such goals are targets relating to each of the indicators to be achieved by the plant over a predetermined period of operation. The current process of defining these goals is carried out by experts in a subjective way, based on actual data from the plant, and comparison with global indices. Artificial neural networks are computational techniques that present a mathematical model inspired by the neural structure of intelligent organisms that acquire knowledge through experience. This paper proposes an artificial neural network model aimed at predicting values of goals to be used in the evaluation of safety performance indicators for nuclear power plants. (author)

Artificial neural network model for prediction of safety performance indicators goals in nuclear plants

International Nuclear Information System (INIS)

Souto, Kelling C.; Nunes, Wallace W.; Machado, Marcelo D.

2011-01-01

Safety performance indicators have been developed to provide a quantitative indication of the performance and safety in various industry sectors. These indexes can provide assess to aspects ranging from production, design, and human performance up to management issues in accordance with policy, objectives and goals of the company. The use of safety performance indicators in nuclear power plants around the world is a reality. However, it is necessary to periodically set goal values. Such goals are targets relating to each of the indicators to be achieved by the plant over a predetermined period of operation. The current process of defining these goals is carried out by experts in a subjective way, based on actual data from the plant, and comparison with global indices. Artificial neural networks are computational techniques that present a mathematical model inspired by the neural structure of intelligent organisms that acquire knowledge through experience. This paper proposes an artificial neural network model aimed at predicting values of goals to be used in the evaluation of safety performance indicators for nuclear power plants. (author)

A multimedia exposure assessment methodology for evaluating the performance of the design of structures containing chemical and radioactive wastes

International Nuclear Information System (INIS)

Stephanatos, B.N.; Molholt, B.; Walter, K.P.; MacGregor, A.

1991-01-01

The objectives of this work are to develop a multimedia exposure assessment methodology for the evaluation of existing and future design of structures containing chemical and radioactive wastes and to identify critical parameters for design optimization. The designs are evaluated in terms of their compliance with various federal and state regulatory requirements. Evaluation of the performance of a particular design is presented within the scope of a given exposure pathway. An exposure pathway has four key components: (1) a source and mechanism of chemical release, (2) a transport medium; (3) a point of exposure; and (4) a route of exposure. The first step in the analysis is the characterization of the waste source behavior. The rate and concentration of releases from the source are evaluated using appropriate mathematical models. The migration of radionuclides and chemicals is simulated through each environmental medium to the exposure point. The total exposure to the potential receptor is calculated, and an estimate of the health effects of the exposure is made. Simulation of the movement of radionuclides and chemical wastes from the source to the receptor point includes several processes. If the predicted human exposure to contaminants meets the performance criteria, the design has been validated. Otherwise the structure design is improved to meet the performance criteria. A phased modeling approach is recommended at a particular mixed waste site. A relatively simple model is initially used to pinpoint critical fate and transport processes and design parameters. The second phase of the modeling effort involves the use of more complex and resource intensive fate and transport models. This final step in the modeling process provides more accurate estimates of contaminant concentrations at the point of exposure. Thus the human dose is more accurately predicted, providing better design validation

Predicting Academic Performance Based on Students' Blog and Microblog Posts

NARCIS (Netherlands)

Dascalu, Mihai; Popescu, Elvira; Becheru, Alexandru; Crossley, Scott; Trausan-Matu, Stefan

2016-01-01

This study investigates the degree to which textual complexity indices applied on students’ online contributions, corroborated with a longitudinal analysis performed on their weekly posts, predict academic performance. The source of student writing consists of blog and microblog posts, created in

Performance demonstration of a high-power space-reactor heat-pipe design

International Nuclear Information System (INIS)

Merrigan, M.A.; Martinez, E.H.; Keddy, E.S.; Runyan, J.; Kemme, J.E.

1983-01-01

Performance of a 15.9-mm diam, 2-m long, artery heat pipe has been demonstrated at power levels to 22.6 kW and temperatures to 1500 0 K. The heat pipe employed lithium as a working fluid with distribution wicks and arteries fabricated from 400 mesh Mo-41 wt % Re screen. Molybdenum alloy (TZM) was used for the container. Peak axial power density attained in the testing was 19 kW/cm 2 at 1465 0 K. The corresponding radial flux density in the evaporator region of the heat pipe was 150 W/cm 2 . The extrapolated limit for the heat pipe at its 1500 0 K design point is 30 kW, corresponding to an axial flux density of 25 kW/cm 2 . Sonic and capillary limits for the design were investigated in the 1100 to 1500 0 K temperature range. Excellent agreement of measured and predicted temperature and power levels was observed

Occupational-Specific Strength Predicts Astronaut-Related Task Performance in a Weighted Suit.

Science.gov (United States)

Taylor, Andrew; Kotarsky, Christopher J; Bond, Colin W; Hackney, Kyle J

2018-01-01

Future space missions beyond low Earth orbit will require deconditioned astronauts to perform occupationally relevant tasks within a planetary spacesuit. The prediction of time-to-completion (TTC) of astronaut tasks will be critical for crew safety, autonomous operations, and mission success. This exploratory study determined if the addition of task-specific strength testing to current standard lower body testing would enhance the prediction of TTC in a 1-G test battery. Eight healthy participants completed NASA lower body strength tests, occupationally specific strength tests, and performed six task simulations (hand drilling, construction wrenching, incline walking, collecting weighted samples, and dragging an unresponsive crewmember to safety) in a 48-kg weighted suit. The TTC for each task was recorded and summed to obtain a total TTC for the test battery. Linear regression was used to predict total TTC with two models: 1) NASA lower body strength tests; and 2) NASA lower body strength tests + occupationally specific strength tests. Total TTC of the test battery ranged from 20.2-44.5 min. The lower body strength test alone accounted for 61% of the variability in total TTC. The addition of hand drilling and wrenching strength tests accounted for 99% of the variability in total TTC. Adding occupationally specific strength tests (hand drilling and wrenching) to standard lower body strength tests successfully predicted total TTC in a performance test battery within a weighted suit. Future research should couple these strength tests with higher fidelity task simulations to determine the utility and efficacy of task performance prediction.Taylor A, Kotarsky CJ, Bond CW, Hackney KJ. Occupational-specific strength predicts astronaut-related task performance in a weighted suit. Aerosp Med Hum Perform. 2018; 89(1):58-62.

A Unified Model of Performance for Predicting the Effects of Sleep and Caffeine

Science.gov (United States)

Ramakrishnan, Sridhar; Wesensten, Nancy J.; Kamimori, Gary H.; Moon, James E.; Balkin, Thomas J.; Reifman, Jaques

2016-01-01

Study Objectives: Existing mathematical models of neurobehavioral performance cannot predict the beneficial effects of caffeine across the spectrum of sleep loss conditions, limiting their practical utility. Here, we closed this research gap by integrating a model of caffeine effects with the recently validated unified model of performance (UMP) into a single, unified modeling framework. We then assessed the accuracy of this new UMP in predicting performance across multiple studies. Methods: We hypothesized that the pharmacodynamics of caffeine vary similarly during both wakefulness and sleep, and that caffeine has a multiplicative effect on performance. Accordingly, to represent the effects of caffeine in the UMP, we multiplied a dose-dependent caffeine factor (which accounts for the pharmacokinetics and pharmacodynamics of caffeine) to the performance estimated in the absence of caffeine. We assessed the UMP predictions in 14 distinct laboratory- and field-study conditions, including 7 different sleep-loss schedules (from 5 h of sleep per night to continuous sleep loss for 85 h) and 6 different caffeine doses (from placebo to repeated 200 mg doses to a single dose of 600 mg). Results: The UMP accurately predicted group-average psychomotor vigilance task performance data across the different sleep loss and caffeine conditions (6% caffeine resulted in improved predictions (after caffeine consumption) by up to 70%. Conclusions: The UMP provides the first comprehensive tool for accurate selection of combinations of sleep schedules and caffeine countermeasure strategies to optimize neurobehavioral performance. Citation: Ramakrishnan S, Wesensten NJ, Kamimori GH, Moon JE, Balkin TJ, Reifman J. A unified model of performance for predicting the effects of sleep and caffeine. SLEEP 2016;39(10):1827–1841. PMID:27397562

Calibration between Undergraduate Students' Prediction of and Actual Performance: The Role of Gender and Performance Attributions

Science.gov (United States)

Gutierrez, Antonio P.; Price, Addison F.

2017-01-01

This study investigated changes in male and female students' prediction and postdiction calibration accuracy and bias scores, and the predictive effects of explanatory styles on these variables beyond gender. Seventy undergraduate students rated their confidence in performance before and after a 40-item exam. There was an improvement in students'…

On predicting student performance using low-rank matrix factorization techniques

DEFF Research Database (Denmark)

Lorenzen, Stephan Sloth; Pham, Dang Ninh; Alstrup, Stephen

2017-01-01

Predicting the score of a student is one of the important problems in educational data mining. The scores given by an individual student reflect how a student understands and applies the knowledge conveyed in class. A reliable performance prediction enables teachers to identify weak students...... that require remedial support, generate adaptive hints, and improve the learning of students. This work focuses on predicting the score of students in the quiz system of the Clio Online learning platform, the largest Danish supplier of online learning materials, covering 90% of Danish elementary schools...... and the current version of the data set is very sparse, the very low-rank approximation can capture enough information. This means that the simple baseline approach achieves similar performance compared to other advanced methods. In future work, we will restrict the quiz data set, e.g. only including quizzes...

MHA admission criteria and program performance: do they predict career performance?

Science.gov (United States)

Porter, J; Galfano, V J

1987-01-01

The purpose of this study was to determine to what extent admission criteria predict graduate school and career performance. The study also analyzed which objective and subjective criteria served as the best predictors. MHA graduates of the University of Minnesota from 1974 to 1977 were surveyed to assess career performance. Student files served as the data base on admission criteria and program performance. Career performance was measured by four variables: total compensation, satisfaction, fiscal responsibility, and level of authority. High levels of MHA program performance were associated with women who had high undergraduate GPAs from highly selective undergraduate colleges, were undergraduate business majors, and participated in extracurricular activities. High levels of compensation were associated with relatively low undergraduate GPAs, high levels of participation in undergraduate extracurricular activities, and being single at admission to graduate school. Admission to MHA programs should be based upon both objective and subjective criteria. Emphasis should be placed upon the selection process for MHA students since admission criteria are shown to explain 30 percent of the variability in graduate program performance, and as much as 65 percent of the variance in level of position authority.

Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort.

Science.gov (United States)

Gao, Ying-Duo; Hu, Yuan; Crespo, Alejandro; Wang, Deping; Armacost, Kira A; Fells, James I; Fradera, Xavier; Wang, Hongwu; Wang, Huijun; Sherborne, Brad; Verras, Andreas; Peng, Zhengwei

2018-01-01

The 2016 D3R Grand Challenge 2 includes both pose and affinity or ranking predictions. This article is focused exclusively on affinity predictions submitted to the D3R challenge from a collaborative effort of the modeling and informatics group. Our submissions include ranking of 102 ligands covering 4 different chemotypes against the FXR ligand binding domain structure, and the relative binding affinity predictions of the two designated free energy subsets of 15 and 18 compounds. Using all the complex structures prepared in the same way allowed us to cover many types of workflows and compare their performances effectively. We evaluated typical workflows used in our daily structure-based design modeling support, which include docking scores, force field-based scores, QM/MM, MMGBSA, MD-MMGBSA, and MacroModel interaction energy estimations. The best performing methods for the two free energy subsets are discussed. Our results suggest that affinity ranking still remains very challenging; that the knowledge of more structural information does not necessarily yield more accurate predictions; and that visual inspection and human intervention are considerably important for ranking. Knowledge of the mode of action and protein flexibility along with visualization tools that depict polar and hydrophobic maps are very useful for visual inspection. QM/MM-based workflows were found to be powerful in affinity ranking and are encouraged to be applied more often. The standardized input and output enable systematic analysis and support methodology development and improvement for high level blinded predictions.

Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort

Science.gov (United States)

Gao, Ying-Duo; Hu, Yuan; Crespo, Alejandro; Wang, Deping; Armacost, Kira A.; Fells, James I.; Fradera, Xavier; Wang, Hongwu; Wang, Huijun; Sherborne, Brad; Verras, Andreas; Peng, Zhengwei

2018-01-01

The 2016 D3R Grand Challenge 2 includes both pose and affinity or ranking predictions. This article is focused exclusively on affinity predictions submitted to the D3R challenge from a collaborative effort of the modeling and informatics group. Our submissions include ranking of 102 ligands covering 4 different chemotypes against the FXR ligand binding domain structure, and the relative binding affinity predictions of the two designated free energy subsets of 15 and 18 compounds. Using all the complex structures prepared in the same way allowed us to cover many types of workflows and compare their performances effectively. We evaluated typical workflows used in our daily structure-based design modeling support, which include docking scores, force field-based scores, QM/MM, MMGBSA, MD-MMGBSA, and MacroModel interaction energy estimations. The best performing methods for the two free energy subsets are discussed. Our results suggest that affinity ranking still remains very challenging; that the knowledge of more structural information does not necessarily yield more accurate predictions; and that visual inspection and human intervention are considerably important for ranking. Knowledge of the mode of action and protein flexibility along with visualization tools that depict polar and hydrophobic maps are very useful for visual inspection. QM/MM-based workflows were found to be powerful in affinity ranking and are encouraged to be applied more often. The standardized input and output enable systematic analysis and support methodology development and improvement for high level blinded predictions.

Performance analysis and prediction in triathlon.

Science.gov (United States)

Ofoghi, Bahadorreza; Zeleznikow, John; Macmahon, Clare; Rehula, Jan; Dwyer, Dan B

2016-01-01

Performance in triathlon is dependent upon factors that include somatotype, physiological capacity, technical proficiency and race strategy. Given the multidisciplinary nature of triathlon and the interaction between each of the three race components, the identification of target split times that can be used to inform the design of training plans and race pacing strategies is a complex task. The present study uses machine learning techniques to analyse a large database of performances in Olympic distance triathlons (2008-2012). The analysis reveals patterns of performance in five components of triathlon (three race "legs" and two transitions) and the complex relationships between performance in each component and overall performance in a race. The results provide three perspectives on the relationship between performance in each component of triathlon and the final placing in a race. These perspectives allow the identification of target split times that are required to achieve a certain final place in a race and the opportunity to make evidence-based decisions about race tactics in order to optimise performance.

Prediction of Human Performance Using Electroencephalography under Different Indoor Room Temperatures

Science.gov (United States)

Zhang, Tinghe; Mao, Zijing; Xu, Xiaojing; Zhang, Lin; Pack, Daniel J.; Dong, Bing; Huang, Yufei

2018-01-01

Varying indoor environmental conditions is known to affect office worker’s performance; wherein past research studies have reported the effects of unfavorable indoor temperature and air quality causing sick building syndrome (SBS) among office workers. Thus, investigating factors that can predict performance in changing indoor environments have become a highly important research topic bearing significant impact in our society. While past research studies have attempted to determine predictors for performance, they do not provide satisfactory prediction ability. Therefore, in this preliminary study, we attempt to predict performance during office-work tasks triggered by different indoor room temperatures (22.2 °C and 30 °C) from human brain signals recorded using electroencephalography (EEG). Seven participants were recruited, from whom EEG, skin temperature, heart rate and thermal survey questionnaires were collected. Regression analyses were carried out to investigate the effectiveness of using EEG power spectral densities (PSD) as predictors of performance. Our results indicate EEG PSDs as predictors provide the highest R2 (> 0.70), that is 17 times higher than using other physiological signals as predictors and is more robust. Finally, the paper provides insight on the selected predictors based on brain activity patterns for low- and high-performance levels under different indoor-temperatures. PMID:29690601

Performance Design as Education of Desire

DEFF Research Database (Denmark)

Pedersen, Michael Haldrup; Petersen, Franziska Bork

a discipline. Such a utopian PD would be an institution without borders. A mobilized and mobilizing institution enjoying an unruly, symbiotic or even parasitic metabolism with academic faculties (art, Geisteswissenschaft, technology, science) and sites for performance (bodies, home, workplace, city, planet......Confronted with the ubiquitous presence of preprogramed desires we propose Performance Design as a utopian institution for the education of desire. The utopian education of desire offers a potential and systematic creation of spaces that enable us “to imagine wanting something else, something...... qualitatively different” (Levitas 2013: 113). PD is uniquely suited to such an educational task, because it can function as a framework for not only designing alternative ways of being through affective interventions and estrangements, but also playing them out in performance. A modus operandi rather than...

Final Technical Report: Increasing Prediction Accuracy.

Energy Technology Data Exchange (ETDEWEB)

King, Bruce Hardison [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hansen, Clifford [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Stein, Joshua [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-12-01

PV performance models are used to quantify the value of PV plants in a given location. They combine the performance characteristics of the system, the measured or predicted irradiance and weather at a site, and the system configuration and design into a prediction of the amount of energy that will be produced by a PV system. These predictions must be as accurate as possible in order for finance charges to be minimized. Higher accuracy equals lower project risk. The Increasing Prediction Accuracy project at Sandia focuses on quantifying and reducing uncertainties in PV system performance models.

Computational Model-Based Prediction of Human Episodic Memory Performance Based on Eye Movements

Science.gov (United States)

Sato, Naoyuki; Yamaguchi, Yoko

Subjects' episodic memory performance is not simply reflected by eye movements. We use a ‘theta phase coding’ model of the hippocampus to predict subjects' memory performance from their eye movements. Results demonstrate the ability of the model to predict subjects' memory performance. These studies provide a novel approach to computational modeling in the human-machine interface.

Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of Pakistan

Directory of Open Access Journals (Sweden)

Senol Celik

Full Text Available ABSTRACT The present study aimed at comparing predictive performance of some data mining algorithms (CART, CHAID, Exhaustive CHAID, MARS, MLP, and RBF in biometrical data of Mengali rams. To compare the predictive capability of the algorithms, the biometrical data regarding body (body length, withers height, and heart girth and testicular (testicular length, scrotal length, and scrotal circumference measurements of Mengali rams in predicting live body weight were evaluated by most goodness of fit criteria. In addition, age was considered as a continuous independent variable. In this context, MARS data mining algorithm was used for the first time to predict body weight in two forms, without (MARS_1 and with interaction (MARS_2 terms. The superiority order in the predictive accuracy of the algorithms was found as CART > CHAID ≈ Exhaustive CHAID > MARS_2 > MARS_1 > RBF > MLP. Moreover, all tested algorithms provided a strong predictive accuracy for estimating body weight. However, MARS is the only algorithm that generated a prediction equation for body weight. Therefore, it is hoped that the available results might present a valuable contribution in terms of predicting body weight and describing the relationship between the body weight and body and testicular measurements in revealing breed standards and the conservation of indigenous gene sources for Mengali sheep breeding. Therefore, it will be possible to perform more profitable and productive sheep production. Use of data mining algorithms is useful for revealing the relationship between body weight and testicular traits in describing breed standards of Mengali sheep.

Integrated Design Software Predicts the Creep Life of Monolithic Ceramic Components

Science.gov (United States)

1996-01-01

Significant improvements in propulsion and power generation for the next century will require revolutionary advances in high-temperature materials and structural design. Advanced ceramics are candidate materials for these elevated-temperature applications. As design protocols emerge for these material systems, designers must be aware of several innate features, including the degrading ability of ceramics to carry sustained load. Usually, time-dependent failure in ceramics occurs because of two different, delayedfailure mechanisms: slow crack growth and creep rupture. Slow crack growth initiates at a preexisting flaw and continues until a critical crack length is reached, causing catastrophic failure. Creep rupture, on the other hand, occurs because of bulk damage in the material: void nucleation and coalescence that eventually leads to macrocracks which then propagate to failure. Successful application of advanced ceramics depends on proper characterization of material behavior and the use of an appropriate design methodology. The life of a ceramic component can be predicted with the NASA Lewis Research Center's Ceramics Analysis and Reliability Evaluation of Structures (CARES) integrated design programs. CARES/CREEP determines the expected life of a component under creep conditions, and CARES/LIFE predicts the component life due to fast fracture and subcritical crack growth. The previously developed CARES/LIFE program has been used in numerous industrial and Government applications.

Predicting Silk Fiber Mechanical Properties through Multiscale Simulation and Protein Design.

Science.gov (United States)

Rim, Nae-Gyune; Roberts, Erin G; Ebrahimi, Davoud; Dinjaski, Nina; Jacobsen, Matthew M; Martín-Moldes, Zaira; Buehler, Markus J; Kaplan, David L; Wong, Joyce Y

2017-08-14

Silk is a promising material for biomedical applications, and much research is focused on how application-specific, mechanical properties of silk can be designed synthetically through proper amino acid sequences and processing parameters. This protocol describes an iterative process between research disciplines that combines simulation, genetic synthesis, and fiber analysis to better design silk fibers with specific mechanical properties. Computational methods are used to assess the protein polymer structure as it forms an interconnected fiber network through shearing and how this process affects fiber mechanical properties. Model outcomes are validated experimentally with the genetic design of protein polymers that match the simulation structures, fiber fabrication from these polymers, and mechanical testing of these fibers. Through iterative feedback between computation, genetic synthesis, and fiber mechanical testing, this protocol will enable a priori prediction capability of recombinant material mechanical properties via insights from the resulting molecular architecture of the fiber network based entirely on the initial protein monomer composition. This style of protocol may be applied to other fields where a research team seeks to design a biomaterial with biomedical application-specific properties. This protocol highlights when and how the three research groups (simulation, synthesis, and engineering) should be interacting to arrive at the most effective method for predictive design of their material.

Designing Second Language Performance Assessments. Technical Report.

Science.gov (United States)

Norris, John M.; Brown, James Dean; Hudson, Thom; Yoshioka, Jim

This technical report focuses on the decision-making potential provided by second language performance assessments. First, performance assessment is situated within the broader discussion of alternatives in language assessment and in educational assessment in general. Next, issues in performance assessment design, implementation, reliability, and…

Do physiological measures predict selected CrossFit(®) benchmark performance?

Science.gov (United States)

Butcher, Scotty J; Neyedly, Tyler J; Horvey, Karla J; Benko, Chad R

2015-01-01

CrossFit(®) is a new but extremely popular method of exercise training and competition that involves constantly varied functional movements performed at high intensity. Despite the popularity of this training method, the physiological determinants of CrossFit performance have not yet been reported. The purpose of this study was to determine whether physiological and/or muscle strength measures could predict performance on three common CrossFit "Workouts of the Day" (WODs). Fourteen CrossFit Open or Regional athletes completed, on separate days, the WODs "Grace" (30 clean and jerks for time), "Fran" (three rounds of thrusters and pull-ups for 21, 15, and nine repetitions), and "Cindy" (20 minutes of rounds of five pull-ups, ten push-ups, and 15 bodyweight squats), as well as the "CrossFit Total" (1 repetition max [1RM] back squat, overhead press, and deadlift), maximal oxygen consumption (VO2max), and Wingate anaerobic power/capacity testing. Performance of Grace and Fran was related to whole-body strength (CrossFit Total) (r=-0.88 and -0.65, respectively) and anaerobic threshold (r=-0.61 and -0.53, respectively); however, whole-body strength was the only variable to survive the prediction regression for both of these WODs (R (2)=0.77 and 0.42, respectively). There were no significant associations or predictors for Cindy. CrossFit benchmark WOD performance cannot be predicted by VO2max, Wingate power/capacity, or either respiratory compensation or anaerobic thresholds. Of the data measured, only whole-body strength can partially explain performance on Grace and Fran, although anaerobic threshold also exhibited association with performance. Along with their typical training, CrossFit athletes should likely ensure an adequate level of strength and aerobic endurance to optimize performance on at least some benchmark WODs.

Do physiological measures predict selected CrossFit® benchmark performance?

Science.gov (United States)

Butcher, Scotty J; Neyedly, Tyler J; Horvey, Karla J; Benko, Chad R

2015-01-01

Purpose CrossFit® is a new but extremely popular method of exercise training and competition that involves constantly varied functional movements performed at high intensity. Despite the popularity of this training method, the physiological determinants of CrossFit performance have not yet been reported. The purpose of this study was to determine whether physiological and/or muscle strength measures could predict performance on three common CrossFit “Workouts of the Day” (WODs). Materials and methods Fourteen CrossFit Open or Regional athletes completed, on separate days, the WODs “Grace” (30 clean and jerks for time), “Fran” (three rounds of thrusters and pull-ups for 21, 15, and nine repetitions), and “Cindy” (20 minutes of rounds of five pull-ups, ten push-ups, and 15 bodyweight squats), as well as the “CrossFit Total” (1 repetition max [1RM] back squat, overhead press, and deadlift), maximal oxygen consumption (VO2max), and Wingate anaerobic power/capacity testing. Results Performance of Grace and Fran was related to whole-body strength (CrossFit Total) (r=−0.88 and −0.65, respectively) and anaerobic threshold (r=−0.61 and −0.53, respectively); however, whole-body strength was the only variable to survive the prediction regression for both of these WODs (R2=0.77 and 0.42, respectively). There were no significant associations or predictors for Cindy. Conclusion CrossFit benchmark WOD performance cannot be predicted by VO2max, Wingate power/capacity, or either respiratory compensation or anaerobic thresholds. Of the data measured, only whole-body strength can partially explain performance on Grace and Fran, although anaerobic threshold also exhibited association with performance. Along with their typical training, CrossFit athletes should likely ensure an adequate level of strength and aerobic endurance to optimize performance on at least some benchmark WODs. PMID:26261428

Development of an Active Solar Crop Dryer: Design Analysis and Performance Evaluation

International Nuclear Information System (INIS)

Itodo, I. N.; Adewole, A.M.; Edemaku, S.K.

2002-01-01

A forced convection indirect solar dryer powered by a PVC module was designed and evaluated. The performance of the dryer was poor; its drying rate, collector and system drying efficiency were 0.74 kg/day, 12% and 10% respectively. The dryer was redesigned and modified into a direct forced convection type- Its design analysis and performance evaluation was undertaken by drying mashed cassava. The drying rate, system drying collector and pick-up efficiencies were 1,6 kg/day (14%/day), 9%, 46% and 29% respectively. Comparatively, the drying rate for sun drying was 0.9 kg/day. The collector efficiency compared very well to the designed value of 48% and may not need further improvement. The pick-up efficiency also compared well with typical averages for this dryer type. The drying rate and system drying efficiency Indicate the need for further development of this dryer. Prediction equations were developed from the results of measured differences in collector, dryer and ambient air temperatures plotted on graphs and applying regression. It is recommended that the volumetric air-flow rate across the drying unit should he improved by affecting the tan speed and air inlet area of the dryer. The improved dryer will subsequently be compared to a natural convection dryer so that an appropriate dryer technology can be recommended for the rural small-scale farmers

KIPT accelerator-driven system design and performance

International Nuclear Information System (INIS)

Gohar, Y.; Bolshinsky, I.; Karnaukhov, I.

2015-01-01

Argonne National Laboratory (ANL) of the US is collaborating with the Kharkov Institute of Physics and Technology (KIPT) of Ukraine to develop and construct a neutron source facility. The facility is planned to produce medical isotopes, train young nuclear professionals, support Ukraine's nuclear industry and provide capability to perform reactor physics, material research, and basic science experiments. It consists of a subcritical assembly with low-enriched uranium fuel driven with an electron accelerator. The target design utilises tungsten or natural uranium for neutron production through photonuclear reactions from the Bremsstrahlung radiation generated by 100-MeV electrons. The accelerator electron beam power is 100 KW. The neutron source intensity, spectrum, and spatial distribution have been studied as a function of the electron beam parameters to maximise the neutron yield and satisfy different engineering requirements. Physics, thermal-hydraulics, and thermal-stress analyses were performed and iterated to maximise the neutron source strength and to minimise the maximum temperature and the thermal stress in the target materials. The subcritical assembly is designed to obtain the highest possible neutron flux intensity with an effective neutron multiplication factor of <0.98. Different fuel and reflector materials are considered for the subcritical assembly design. The mechanical design of the facility has been developed to maximise its utility and minimise the time for replacing the target, fuel, and irradiation cassettes by using simple and efficient procedures. Shielding analyses were performed to define the dose map around the facility during operation as a function of the heavy concrete shield thickness. Safety, reliability and environmental considerations are included in the facility design. The facility is configured to accommodate future design upgrades and new missions. In addition, it has unique features relative to the other international

Numerical prediction and performance experiment in a deep-well centrifugal pump with different impeller outlet width

Science.gov (United States)

Shi, Weidong; Zhou, Ling; Lu, Weigang; Pei, Bing; Lang, Tao

2013-01-01

The existing research of the deep-well centrifugal pump mainly focuses on reduce the manufacturing cost and improve the pump performance, and how to combine above two aspects together is the most difficult and important topic. In this study, the performances of the deep-well centrifugal pump with four different impeller outlet widths are studied by the numerical, theoretical and experimental methods in this paper. Two stages deep-well centrifugal pump equipped with different impellers are simulated employing the commercial CFD software to solve the Navier-Stokes equations for three-dimensional incompressible steady flow. The sensitivity analyses of the grid size and turbulence model have been performed to improve numerical accuracy. The flow field distributions are acquired and compared under the design operating conditions, including the static pressure, turbulence kinetic energy and velocity. The prototype is manufactured and tested to certify the numerical predicted performance. The numerical results of pump performance are higher than the test results, but their change trends have an acceptable agreement with each other. The performance results indicted that the oversize impeller outlet width leads to poor pump performances and increasing shaft power. Changing the performance of deep-well centrifugal pump by alter impeller outlet width is practicable and convenient, which is worth popularizing in the engineering application. The proposed research enhances the theoretical basis of pump design to improve the performance and reduce the manufacturing cost of deep-well centrifugal pump.

Design and verification of controllers for longitudinal oscillations using optimal control theory and numerical simulation: Predictions for PEP-II

International Nuclear Information System (INIS)

Hindi, H.; Prabhakar, S.; Fox, J.; Teytelman, D.

1997-12-01

The authors present a technique for the design and verification of efficient bunch-by-bunch controllers for damping longitudinal multibunch instabilities. The controllers attempt to optimize the use of available feedback amplifier power--one of the most expensive components of a feedback system--and define the limits of closed loop system performance. The design technique alternates between analytic computation of single bunch optimal controllers and verification on a multibunch numerical simulator. The simulator identifies unstable coupled bunch modes and predicts their growth and damping rates. The results from the simulator are shown to be in reasonable agreement with analytical calculations based on the single bunch model. The technique is then used to evaluate the performance of a variety of controllers proposed for PEP-II

Space Launch System Base Heating Test: Sub-Scale Rocket Engine/Motor Design, Development and Performance Analysis

Science.gov (United States)

Mehta, Manish; Seaford, Mark; Kovarik, Brian; Dufrene, Aaron; Solly, Nathan; Kirchner, Robert; Engel, Carl D.

2014-01-01

The Space Launch System (SLS) base heating test is broken down into two test programs: (1) Pathfinder and (2) Main Test. The Pathfinder Test Program focuses on the design, development, hot-fire test and performance analyses of the 2% sub-scale SLS core-stage and booster element propulsion systems. The core-stage propulsion system is composed of four gaseous oxygen/hydrogen RS-25D model engines and the booster element is composed of two aluminum-based model solid rocket motors (SRMs). The first section of the paper discusses the motivation and test facility specifications for the test program. The second section briefly investigates the internal flow path of the design. The third section briefly shows the performance of the model RS-25D engines and SRMs for the conducted short duration hot-fire tests. Good agreement is observed based on design prediction analysis and test data. This program is a challenging research and development effort that has not been attempted in 40+ years for a NASA vehicle.

Numerical modeling capabilities to predict repository performance

International Nuclear Information System (INIS)

1979-09-01

This report presents a summary of current numerical modeling capabilities that are applicable to the design and performance evaluation of underground repositories for the storage of nuclear waste. The report includes codes that are available in-house, within Golder Associates and Lawrence Livermore Laboratories; as well as those that are generally available within the industry and universities. The first listing of programs are in-house codes in the subject areas of hydrology, solute transport, thermal and mechanical stress analysis, and structural geology. The second listing of programs are divided by subject into the following categories: site selection, structural geology, mine structural design, mine ventilation, hydrology, and mine design/construction/operation. These programs are not specifically designed for use in the design and evaluation of an underground repository for nuclear waste; but several or most of them may be so used

Conceptual Designs for the Performance Improvement of APR1400 SIT and Preliminary Performance Evaluation

International Nuclear Information System (INIS)

Chu, In-Cheol; Kwon, Tae-Soon; Song, Chul-Hwa

2008-01-01

Some evolutionary type PWRs such as APR1400 and APWR adopt advanced safety injection tank (SIT). The SIT of APR1400 has a fluidic device (FD) which passively controls ECC water injection flow rate into reactor coolant system during refill and reflood phases of LB-LOCA (i.e., a high injection flow rate during the refill phase and a low injection flow rate during the reflood phase). The benefit of the FD is the elimination of the function of low pressure safety injection pump from the safety injection system. The flow controlling performance of the APR1400 FD was evaluated using a prototypical full-scale test facility, called VAPER (Valve Performance Evaluation Rig). Even though the performance of the APR1400 FD satisfied major design and licensing requirements, further improvement of the performance is expected such as the extension of total injection period, the delay of nitrogen gas discharge. Several conceptual designs have been being drawn out in order to improve the performance of the APR1400 SIT. The performance of some designs was evaluated using a small scale SIT test rig. The present paper introduces some of the conceptual designs and shows the performance evaluation experimental results

A Unified Model of Performance for Predicting the Effects of Sleep and Caffeine.

Science.gov (United States)

Ramakrishnan, Sridhar; Wesensten, Nancy J; Kamimori, Gary H; Moon, James E; Balkin, Thomas J; Reifman, Jaques

2016-10-01

Existing mathematical models of neurobehavioral performance cannot predict the beneficial effects of caffeine across the spectrum of sleep loss conditions, limiting their practical utility. Here, we closed this research gap by integrating a model of caffeine effects with the recently validated unified model of performance (UMP) into a single, unified modeling framework. We then assessed the accuracy of this new UMP in predicting performance across multiple studies. We hypothesized that the pharmacodynamics of caffeine vary similarly during both wakefulness and sleep, and that caffeine has a multiplicative effect on performance. Accordingly, to represent the effects of caffeine in the UMP, we multiplied a dose-dependent caffeine factor (which accounts for the pharmacokinetics and pharmacodynamics of caffeine) to the performance estimated in the absence of caffeine. We assessed the UMP predictions in 14 distinct laboratory- and field-study conditions, including 7 different sleep-loss schedules (from 5 h of sleep per night to continuous sleep loss for 85 h) and 6 different caffeine doses (from placebo to repeated 200 mg doses to a single dose of 600 mg). The UMP accurately predicted group-average psychomotor vigilance task performance data across the different sleep loss and caffeine conditions (6% caffeine resulted in improved predictions (after caffeine consumption) by up to 70%. The UMP provides the first comprehensive tool for accurate selection of combinations of sleep schedules and caffeine countermeasure strategies to optimize neurobehavioral performance. © 2016 Associated Professional Sleep Societies, LLC.

Binding Mode and Induced Fit Predictions for Prospective Computational Drug Design.

Science.gov (United States)

Grebner, Christoph; Iegre, Jessica; Ulander, Johan; Edman, Karl; Hogner, Anders; Tyrchan, Christian

2016-04-25

Computer-aided drug design plays an important role in medicinal chemistry to obtain insights into molecular mechanisms and to prioritize design strategies. Although significant improvement has been made in structure based design, it still remains a key challenge to accurately model and predict induced fit mechanisms. Most of the current available techniques either do not provide sufficient protein conformational sampling or are too computationally demanding to fit an industrial setting. The current study presents a systematic and exhaustive investigation of predicting binding modes for a range of systems using PELE (Protein Energy Landscape Exploration), an efficient and fast protein-ligand sampling algorithm. The systems analyzed (cytochrome P, kinase, protease, and nuclear hormone receptor) exhibit different complexities of ligand induced fit mechanisms and protein dynamics. The results are compared with results from classical molecular dynamics simulations and (induced fit) docking. This study shows that ligand induced side chain rearrangements and smaller to medium backbone movements are captured well in PELE. Large secondary structure rearrangements, however, remain challenging for all employed techniques. Relevant binding modes (ligand heavy atom RMSD PELE method within a few hours of simulation, positioning PELE as a tool applicable for rapid drug design cycles.

Dataset size and composition impact the reliability of performance benchmarks for peptide-MHC binding predictions

DEFF Research Database (Denmark)

Kim, Yohan; Sidney, John; Buus, Søren

2014-01-01

Background: It is important to accurately determine the performance of peptide: MHC binding predictions, as this enables users to compare and choose between different prediction methods and provides estimates of the expected error rate. Two common approaches to determine prediction performance...... are cross-validation, in which all available data are iteratively split into training and testing data, and the use of blind sets generated separately from the data used to construct the predictive method. In the present study, we have compared cross-validated prediction performances generated on our last...

Goal orientation and work role performance: predicting adaptive and proactive work role performance through self-leadership strategies.

Science.gov (United States)

Marques-Quinteiro, Pedro; Curral, Luís Alberto

2012-01-01

This article explores the relationship between goal orientation, self-leadership dimensions, and adaptive and proactive work role performances. The authors hypothesize that learning orientation, in contrast to performance orientation, positively predicts proactive and adaptive work role performances and that this relationship is mediated by self-leadership behavior-focused strategies. It is posited that self-leadership natural reward strategies and thought pattern strategies are expected to moderate this relationship. Workers (N = 108) from a software company participated in this study. As expected, learning orientation did predict adaptive and proactive work role performance. Moreover, in the relationship between learning orientation and proactive work role performance through self-leadership behavior-focused strategies, a moderated mediation effect was found for self-leadership natural reward and thought pattern strategies. In the end, the authors discuss the results and implications are discussed and future research directions are proposed.

Design prediction for long term stress rupture service of composite pressure vessels

Science.gov (United States)

Robinson, Ernest Y.

1992-01-01

Extensive stress rupture studies on glass composites and Kevlar composites were conducted by the Lawrence Radiation Laboratory beginning in the late 1960's and extending to about 8 years in some cases. Some of the data from these studies published over the years were incomplete or were tainted by spurious failures, such as grip slippage. Updated data sets were defined for both fiberglass and Kevlar composite stand test specimens. These updated data are analyzed in this report by a convenient form of the bivariate Weibull distribution, to establish a consistent set of design prediction charts that may be used as a conservative basis for predicting the stress rupture life of composite pressure vessels. The updated glass composite data exhibit an invariant Weibull modulus with lifetime. The data are analyzed in terms of homologous service load (referenced to the observed median strength). The equations relating life, homologous load, and probability are given, and corresponding design prediction charts are presented. A similar approach is taken for Kevlar composites, where the updated stand data do show a turndown tendency at long life accompanied by a corresponding change (increase) of the Weibull modulus. The turndown characteristic is not present in stress rupture test data of Kevlar pressure vessels. A modification of the stress rupture equations is presented to incorporate a latent, but limited, strength drop, and design prediction charts are presented that incorporate such behavior. The methods presented utilize Cartesian plots of the probability distributions (which are a more natural display for the design engineer), based on median normalized data that are independent of statistical parameters and are readily defined for any set of test data.

Dynamic Algorithm for LQGPC Predictive Control

DEFF Research Database (Denmark)

Hangstrup, M.; Ordys, A.W.; Grimble, M.J.

1998-01-01

In this paper the optimal control law is derived for a multi-variable state space Linear Quadratic Gaussian Predictive Controller (LQGPC). A dynamic performance index is utilized resulting in an optimal steady state controller. Knowledge of future reference values is incorporated into the control......In this paper the optimal control law is derived for a multi-variable state space Linear Quadratic Gaussian Predictive Controller (LQGPC). A dynamic performance index is utilized resulting in an optimal steady state controller. Knowledge of future reference values is incorporated...... into the controller design and the solution is derived using the method of Lagrange multipliers. It is shown how well-known GPC controller can be obtained as a special case of the LQGPC controller design. The important advantage of using the LQGPC framework for designing predictive, e.g. GPS is that LQGPC enables...

Influence of covariate distribution on the predictive performance of pharmacokinetic models in paediatric research

Science.gov (United States)

Piana, Chiara; Danhof, Meindert; Della Pasqua, Oscar

2014-01-01

Aims The accuracy of model-based predictions often reported in paediatric research has not been thoroughly characterized. The aim of this exercise is therefore to evaluate the role of covariate distributions when a pharmacokinetic model is used for simulation purposes. Methods Plasma concentrations of a hypothetical drug were simulated in a paediatric population using a pharmacokinetic model in which body weight was correlated with clearance and volume of distribution. Two subgroups of children were then selected from the overall population according to a typical study design, in which pre-specified body weight ranges (10–15 kg and 30–40 kg) were used as inclusion criteria. The simulated data sets were then analyzed using non-linear mixed effects modelling. Model performance was assessed by comparing the accuracy of AUC predictions obtained for each subgroup, based on the model derived from the overall population and by extrapolation of the model parameters across subgroups. Results Our findings show that systemic exposure as well as pharmacokinetic parameters cannot be accurately predicted from the pharmacokinetic model obtained from a population with a different covariate range from the one explored during model building. Predictions were accurate only when a model was used for prediction in a subgroup of the initial population. Conclusions In contrast to current practice, the use of pharmacokinetic modelling in children should be limited to interpolations within the range of values observed during model building. Furthermore, the covariate point estimate must be kept in the model even when predictions refer to a subset different from the original population. PMID:24433411

Predicting work Performance through selection interview ratings and Psychological assessment

Directory of Open Access Journals (Sweden)

Liziwe Nzama

2008-11-01

Full Text Available The aim of the study was to establish whether selection interviews used in conjunction with psychological assessments of personality traits and cognitive functioning contribute to predicting work performance. The sample consisted of 102 managers who were appointed recently in a retail organisation. The independent variables were selection interview ratings obtained on the basis of structured competency-based interview schedules by interviewing panels, fve broad dimensions of personality defned by the Five Factor Model as measured by the 15 Factor Questionnaire (15FQ+, and cognitive processing variables (current level of work, potential level of work, and 12 processing competencies measured by the Cognitive Process Profle (CPP. Work performance was measured through annual performance ratings that focused on measurable outputs of performance objectives. Only two predictor variables correlated statistically signifcantly with the criterion variable, namely interview ratings (r = 0.31 and CPP Verbal Abstraction (r = 0.34. Following multiple regression, only these variables contributed signifcantly to predicting work performance, but only 17.8% of the variance of the criterion was accounted for.

Influence of the radial-inflow turbine efficiency prediction on the design and analysis of the Organic Rankine Cycle (ORC) system

International Nuclear Information System (INIS)

Song, Jian; Gu, Chun-wei; Ren, Xiaodong

2016-01-01

Highlights: • The efficiency prediction is based on the velocity triangle and loss models. • The efficiency selection has a big influence on the working fluid selection. • The efficiency selection has a big influence on system parameter determination. - Abstract: The radial-inflow turbine is a common choice for the power output in the Organic Rankine Cycle (ORC) system. Its efficiency is related to the working fluid property and the system operating condition. Generally, the radial-inflow turbine efficiency is assumed to be a constant value in the conventional ORC system analysis. Few studies focus on the influence of the radial-inflow turbine efficiency selection on the system design and analysis. Actually, the ORC system design and the radial-inflow turbine design are coupled with each other. Different thermal parameters of the ORC system would lead to different radial-inflow turbine design and then different turbine efficiency, and vice versa. Therefore, considering the radial-inflow turbine efficiency prediction in the ORC system design can enhance its reliability and accuracy. In this paper, a one-dimensional analysis model for the radial-inflow turbine in the ORC system is presented. The radial-inflow turbine efficiency prediction in this model is based on the velocity triangle and loss models, rather than a constant efficiency assumption. The influence of the working fluid property and the system operating condition on the turbine performance is evaluated. The thermodynamic analysis of the ORC system with a model predicted turbine efficiency and a constant turbine efficiency is conducted and the results are compared with each other. It indicates that the turbine efficiency selection has a significant influence on the working fluid selection and the system parameter determination.

ExaSAT: An exascale co-design tool for performance modeling

International Nuclear Information System (INIS)

Unat, Didem; Chan, Cy; Zhang, Weiqun; Williams, Samuel; Bachan, John

2015-01-01

One of the emerging challenges to designing HPC systems is understanding and projecting the requirements of exascale applications. In order to determine the performance consequences of different hardware designs, analytic models are essential because they can provide fast feedback to the co-design centers and chip designers without costly simulations. However, current attempts to analytically model program performance typically rely on the user manually specifying a performance model. Here we introduce the ExaSAT framework that automates the extraction of parameterized performance models directly from source code using compiler analysis. The parameterized analytic model enables quantitative evaluation of a broad range of hardware design trade-offs and software optimizations on a variety of different performance metrics, with a primary focus on data movement as a metric. Finally, we demonstrate the ExaSAT framework’s ability to perform deep code analysis of a proxy application from the Department of Energy Combustion Co-design Center to illustrate its value to the exascale co-design process. ExaSAT analysis provides insights into the hardware and software trade-offs and lays the groundwork for exploring a more targeted set of design points using cycle-accurate architectural simulators.

Predicting Students' Performance in the Senior Secondary ...

African Journals Online (AJOL)

cce

correlation design. ... the JSC examinations were a good predictor of performance at SSC ..... Table 12: Effects of the Independent Variables (JSCE 2000) on the .... JAMB Brochure, Abuja: Joint Admissions and Matriculation Examinations, 2-3.

Falling in the elderly: Do statistical models matter for performance criteria of fall prediction? Results from two large population-based studies.

Science.gov (United States)

Kabeshova, Anastasiia; Launay, Cyrille P; Gromov, Vasilii A; Fantino, Bruno; Levinoff, Elise J; Allali, Gilles; Beauchet, Olivier

2016-01-01

To compare performance criteria (i.e., sensitivity, specificity, positive predictive value, negative predictive value, area under receiver operating characteristic curve and accuracy) of linear and non-linear statistical models for fall risk in older community-dwellers. Participants were recruited in two large population-based studies, "Prévention des Chutes, Réseau 4" (PCR4, n=1760, cross-sectional design, retrospective collection of falls) and "Prévention des Chutes Personnes Agées" (PCPA, n=1765, cohort design, prospective collection of falls). Six linear statistical models (i.e., logistic regression, discriminant analysis, Bayes network algorithm, decision tree, random forest, boosted trees), three non-linear statistical models corresponding to artificial neural networks (multilayer perceptron, genetic algorithm and neuroevolution of augmenting topologies [NEAT]) and the adaptive neuro fuzzy interference system (ANFIS) were used. Falls ≥1 characterizing fallers and falls ≥2 characterizing recurrent fallers were used as outcomes. Data of studies were analyzed separately and together. NEAT and ANFIS had better performance criteria compared to other models. The highest performance criteria were reported with NEAT when using PCR4 database and falls ≥1, and with both NEAT and ANFIS when pooling data together and using falls ≥2. However, sensitivity and specificity were unbalanced. Sensitivity was higher than specificity when identifying fallers, whereas the converse was found when predicting recurrent fallers. Our results showed that NEAT and ANFIS were non-linear statistical models with the best performance criteria for the prediction of falls but their sensitivity and specificity were unbalanced, underscoring that models should be used respectively for the screening of fallers and the diagnosis of recurrent fallers. Copyright © 2015 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

The Curvilinear Association between Performance Measurement System Design and Strategic Performance

DEFF Research Database (Denmark)

Schneider, Melanie L.; Mahlendorf, Matthias D.; Schäffer, Utz

This paper reconciles prior research regarding beneficial and detrimental effects of performance measurement system (PMS) design on performance by arguing for a curvilinear association. By taking the too-much-of-a-good-thing effect as a starting point, we challenge the assumption of a linear...

Performance of a solar chimney by varying design parameters

CSIR Research Space (South Africa)

Kumirai, T

2015-08-01

Full Text Available the design of solar chimneys to ensure optimal performance. The purpose of this chapter is to discuss the performance of an example solar chimney by varying the design parameters and examining their effects on the interior ventilation performance... chimney by varying design parameters Tichaona Kumirai, Researcher, Built Environment CSIR Jan-Hendrik Grobler, DPSS CSIR Dr D.C.U. Conradie, Senior researcher, Built Environment CSIR 1 Introduction Trombe walls and solar chimneys are not widely...

Design of a new PID controller using predictive functional control optimization for chamber pressure in a coke furnace.

Science.gov (United States)

Zhang, Jianming

2017-03-01

An improved proportional-integral-derivative (PID) controller based on predictive functional control (PFC) is proposed and tested on the chamber pressure in an industrial coke furnace. The proposed design is motivated by the fact that PID controllers for industrial processes with time delay may not achieve the desired control performance because of the unavoidable model/plant mismatches, while model predictive control (MPC) is suitable for such situations. In this paper, PID control and PFC algorithm are combined to form a new PID controller that has the basic characteristic of PFC algorithm and at the same time, the simple structure of traditional PID controller. The proposed controller was tested in terms of set-point tracking and disturbance rejection, where the obtained results showed that the proposed controller had the better ensemble performance compared with traditional PID controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Predicting Arithmetical Achievement from Neuro-Psychological Performance: A Longitudinal Study.

Science.gov (United States)

Fayol, Michel; Barrouillet, Pierre; Marinthe, Catherine

1998-01-01

Assessed whether performances of 5- and 6-year olds in arithmetic tests can be predicted from their performances in neuropsychological tests. Participants completed neuropsychological, drawing, and arithmetic tests at 5 and 6 years of age. Findings at older age were correctly assumed by conclusions of first evaluation. (LBT)

Short-term prediction of solar energy in Saudi Arabia using automated-design fuzzy logic systems.

Science.gov (United States)

Almaraashi, Majid

2017-01-01

Solar energy is considered as one of the main sources for renewable energy in the near future. However, solar energy and other renewable energy sources have a drawback related to the difficulty in predicting their availability in the near future. This problem affects optimal exploitation of solar energy, especially in connection with other resources. Therefore, reliable solar energy prediction models are essential to solar energy management and economics. This paper presents work aimed at designing reliable models to predict the global horizontal irradiance (GHI) for the next day in 8 stations in Saudi Arabia. The designed models are based on computational intelligence methods of automated-design fuzzy logic systems. The fuzzy logic systems are designed and optimized with two models using fuzzy c-means clustering (FCM) and simulated annealing (SA) algorithms. The first model uses FCM based on the subtractive clustering algorithm to automatically design the predictor fuzzy rules from data. The second model is using FCM followed by simulated annealing algorithm to enhance the prediction accuracy of the fuzzy logic system. The objective of the predictor is to accurately predict next-day global horizontal irradiance (GHI) using previous-day meteorological and solar radiation observations. The proposed models use observations of 10 variables of measured meteorological and solar radiation data to build the model. The experimentation and results of the prediction are detailed where the root mean square error of the prediction was approximately 88% for the second model tuned by simulated annealing compared to 79.75% accuracy using the first model. This results demonstrate a good modeling accuracy of the second model despite that the training and testing of the proposed models were carried out using spatially and temporally independent data.

High performance APCS conceptual design and evaluation scoping study

International Nuclear Information System (INIS)

Soelberg, N.; Liekhus, K.; Chambers, A.; Anderson, G.

1998-02-01

This Air Pollution Control System (APCS) Conceptual Design and Evaluation study was conducted to evaluate a high-performance (APC) system for minimizing air emissions from mixed waste thermal treatment systems. Seven variations of high-performance APCS designs were conceptualized using several design objectives. One of the system designs was selected for detailed process simulation using ASPEN PLUS to determine material and energy balances and evaluate performance. Installed system capital costs were also estimated. Sensitivity studies were conducted to evaluate the incremental cost and benefit of added carbon adsorber beds for mercury control, specific catalytic reduction for NO x control, and offgas retention tanks for holding the offgas until sample analysis is conducted to verify that the offgas meets emission limits. Results show that the high-performance dry-wet APCS can easily meet all expected emission limits except for possibly mercury. The capability to achieve high levels of mercury control (potentially necessary for thermally treating some DOE mixed streams) could not be validated using current performance data for mercury control technologies. The engineering approach and ASPEN PLUS modeling tool developed and used in this study identified APC equipment and system performance, size, cost, and other issues that are not yet resolved. These issues need to be addressed in feasibility studies and conceptual designs for new facilities or for determining how to modify existing facilities to meet expected emission limits. The ASPEN PLUS process simulation with current and refined input assumptions and calculations can be used to provide system performance information for decision-making, identifying best options, estimating costs, reducing the potential for emission violations, providing information needed for waste flow analysis, incorporating new APCS technologies in existing designs, or performing facility design and permitting activities

Performance and wake predictions of HAWTs in wind farms

Energy Technology Data Exchange (ETDEWEB)

Leclerc, C.; Masson, C.; Paraschivoiu, I. [Ecole Polytechnique, Montreal (Canada)

1997-12-31

The present contribution proposes and describes a promising way towards performance prediction of an arbitrary array of turbines. It is based on the solution of the time-averaged, steady-state, incompressible Navier-Stokes equations with an appropriate turbulence closure model. The turbines are represented by distributions of momentum sources in the Navier-Stokes equations. In this paper, the applicability and viability of the proposed methodology is demonstrated using an axisymmetric implementation. The k-{epsilon} model has been chosen for the closure of the time-averaged, turbulent flow equations and the properties of the incident flow correspond to those of a neutral atmospheric boundary layer. The proposed mathematical model is solved using a Control-Volume Finite Element Method (CVFEM). Detailed results have been obtained using the proposed method for an isolated wind turbine and for two turbines one behind another. In the case of an isolated turbine, accurate wake velocity deficit predictions are obtained and an increase in power due to atmospheric turbulence is found in agreement with measurements. In the case of two turbines, the proposed methodology provides an appropriate modelling of the wind-turbine wake and a realistic prediction of the performance degradation of the downstream turbine.

Can Medical School Performance Predict Residency Performance? Resident Selection and Predictors of Successful Performance in Obstetrics and Gynecology

Science.gov (United States)

Stohl, Hindi E.; Hueppchen, Nancy A.; Bienstock, Jessica L.

2010-01-01

Background During the evaluation process, Residency Admissions Committees typically gather data on objective and subjective measures of a medical student's performance through the Electronic Residency Application Service, including medical school grades, standardized test scores, research achievements, nonacademic accomplishments, letters of recommendation, the dean's letter, and personal statements. Using these data to identify which medical students are likely to become successful residents in an academic residency program in obstetrics and gynecology is difficult and to date, not well studied. Objective To determine whether objective information in medical students' applications can help predict resident success. Method We performed a retrospective cohort study of all residents who matched into the Johns Hopkins University residency program in obstetrics and gynecology between 1994 and 2004 and entered the program through the National Resident Matching Program as a postgraduate year-1 resident. Residents were independently evaluated by faculty and ranked in 4 groups according to perceived level of success. Applications from residents in the highest and lowest group were abstracted. Groups were compared using the Fisher exact test and the Student t test. Results Seventy-five residents met inclusion criteria and 29 residents were ranked in the highest and lowest quartiles (15 in highest, 14 in lowest). Univariate analysis identified no variables as consistent predictors of resident success. Conclusion In a program designed to train academic obstetrician-gynecologists, objective data from medical students' applications did not correlate with successful resident performance in our obstetrics-gynecology residency program. We need to continue our search for evaluation criteria that can accurately and reliably select the medical students that are best fit for our specialty. PMID:21976076

Verification, validation, and reliability of predictions

International Nuclear Information System (INIS)

Pigford, T.H.; Chambre, P.L.

1987-04-01

The objective of predicting long-term performance should be to make reliable determinations of whether the prediction falls within the criteria for acceptable performance. Establishing reliable predictions of long-term performance of a waste repository requires emphasis on valid theories to predict performance. The validation process must establish the validity of the theory, the parameters used in applying the theory, the arithmetic of calculations, and the interpretation of results; but validation of such performance predictions is not possible unless there are clear criteria for acceptable performance. Validation programs should emphasize identification of the substantive issues of prediction that need to be resolved. Examples relevant to waste package performance are predicting the life of waste containers and the time distribution of container failures, establishing the criteria for defining container failure, validating theories for time-dependent waste dissolution that depend on details of the repository environment, and determining the extent of congruent dissolution of radionuclides in the UO 2 matrix of spent fuel. Prediction and validation should go hand in hand and should be done and reviewed frequently, as essential tools for the programs to design and develop repositories. 29 refs

Predicting Performance on MOOC Assessments using Multi-Regression Models

OpenAIRE

Ren, Zhiyun; Rangwala, Huzefa; Johri, Aditya

2016-01-01

The past few years has seen the rapid growth of data min- ing approaches for the analysis of data obtained from Mas- sive Open Online Courses (MOOCs). The objectives of this study are to develop approaches to predict the scores a stu- dent may achieve on a given grade-related assessment based on information, considered as prior performance or prior ac- tivity in the course. We develop a personalized linear mul- tiple regression (PLMR) model to predict the grade for a student, prior to attempt...

Enhancing human performance in ship operations by modifying global design factors at the design stage

International Nuclear Information System (INIS)

Montewka, Jakub; Goerlandt, Floris; Innes-Jones, Gemma; Owen, Douglas; Hifi, Yasmine; Puisa, Romanas

2017-01-01

Usually the improvements of human performance in the course of ship design process is carried out by modifying local ergonomics, like electronic visualisation and information display systems on the bridge or in the engine control room, stair or hatch covers design. However, the effect of global design factors (GDFs), such as ship motion, whole body vibration and noise, on human performance has not been given attention before. Such knowledge would allow the improvements of human performance by effective design modification on very early stage of ship design process. Therefore, in this paper we introduce probabilistic models linking the effect of GDFs with the human performance suitable for ship design process. As a theoretical basis for modelling human performance the concept of Attention Management is utilized, which combines the theories described by Dynamic Adaptability Model, Cognitive Control Model and Malleable Attentional Resources Theory. Since the analysed field is characterised by a high degree of uncertainty, we adopt a specific modelling technique along with a validation framework that allows uncertainty treatment and helps the potential end-users to gain confidence in the models and the results that they yield. The proposed models are developed with the use Bayesian Belief Networks, which allows systematic translation of the available background knowledge into a coherent network and the uncertainty assessment and treatment. The obtained results are promising as the models are responsive to changes in the GDF nodes as expected. The models may be used as intended by naval architects and vessel designers, to facilitate risk-based ship design. - Highlights: • Models linking the effect of GDFs with the human performance are established. • Three global design factors (GDFs) are considered: ship motion, body vibration, noise. • Attention Management concept as theoretical base is modelled with Bayesian Networks. • Two models are developed that can be

Comparative performance of conventional OPC concrete and HPC designed by densified mixture design algorithm

Science.gov (United States)

Huynh, Trong-Phuoc; Hwang, Chao-Lung; Yang, Shu-Ti

2017-12-01

This experimental study evaluated the performance of normal ordinary Portland cement (OPC) concrete and high-performance concrete (HPC) that were designed by the conventional method (ACI) and densified mixture design algorithm (DMDA) method, respectively. Engineering properties and durability performance of both the OPC and HPC samples were studied using the tests of workability, compressive strength, water absorption, ultrasonic pulse velocity, and electrical surface resistivity. Test results show that the HPC performed good fresh property and further showed better performance in terms of strength and durability as compared to the OPC.

Design of low noise airfoil with high aerodynamic performance for use on small wind turbines

Institute of Scientific and Technical Information of China (English)

Taehyung; KIM; Seungmin; LEE; Hogeon; KIM; Soogab; LEE

2010-01-01

Wind power is one of the most reliable renewable energy sources and internationally installed capacity is increasing radically every year.Although wind power has been favored by the public in general,the problem with the impact of wind turbine noise on people living in the vicinity of the turbines has been increased.Low noise wind turbine design is becoming more and more important as noise is spreading more adverse effect of wind turbine to public.This paper demonstrates the design of 10 kW class wind turbines,each of three blades,a rotor diameter 6.4 m,a rated rotating speed 200 r/min and a rated wind speed 10 m/s.The optimized airfoil is dedicated for the 75% spanwise position because the dominant source of a wind turbine blade is trailing edge noise from the outer 25% of the blade.Numerical computations are performed for incompressible flow and for Mach number at 0.145 and for Reynolds numbers at 1.02×106 with a lift performance,which is resistant to surface contamination and turbulence intensity.The objectives in the design process are to reduce noise emission,while sustaining high aerodynamic efficiency.Dominant broadband noise sources are predicted by semi-empirical formulas composed of the groundwork by Brooks et al.and Lowson associated with typical wind turbine operation conditions.During the airfoil redesign process,the aerodynamic performance is analyzed to reduce the wind turbine power loss.The results obtained from the design process show that the design method is capable of designing airfoils with reduced noise using a commercial 10 kW class wind turbine blade airfoil as a basis.Therefore,the new optimized airfoil showing 2.9 dB reductions of total sound pressure level(SPL) and higher aerodynamic performance are achieved.

Predictive tools for designing new insulins and treatment regimens

DEFF Research Database (Denmark)

Klim, Søren

The thesis deals with the development of "Predictive tools for designing new insulins and treatments regimens" and consists of two parts: A model based approach for bridging properties of new insulin analogues from glucose clamp experiments to meal tolerance tests (MTT) and a second part that des......The thesis deals with the development of "Predictive tools for designing new insulins and treatments regimens" and consists of two parts: A model based approach for bridging properties of new insulin analogues from glucose clamp experiments to meal tolerance tests (MTT) and a second part...... that describes an implemented software program able to handle stochastic differential equations (SDEs) with mixed effects. The thesis is supplemented with scientific papers published during the PhD. Developing an insulin analogue from candidate molecule to a clinical drug consists of a development programme...... and efficacy are investigated. Numerous methods are used to quantify dose and efficacy in Phase II - especially of interest is the 24-hour meal tolerance test as it tries to portray near normal living conditions. Part I describes an integrated model for insulin and glucose which is aimed at simulating 24-hour...

Computerized heat balance models to predict performance of operating nuclear power plants

International Nuclear Information System (INIS)

Breeding, C.L.; Carter, J.C.; Schaefer, R.C.

1983-01-01

The use of computerized heat balance models has greatly enhanced the decision making ability of TVA's Division of Nuclear Power. These models are utilized to predict the effects of various operating modes and to analyze changes in plant performance resulting from turbine cycle equipment modifications with greater speed and accuracy than was possible before. Computer models have been successfully used to optimize plant output by predicting the effects of abnormal condenser circulating water conditions. They were utilized to predict the degradation in performance resulting from installation of a baffle plate assembly to replace damaged low-pressure blading, thereby providing timely information allowing an optimal economic judgement as to when to replace the blading. Future use will be for routine performance test analysis. This paper presents the benefits of utility use of computerized heat balance models

Ski jump takeoff performance predictions for a mixed-flow, remote-lift STOVL aircraft

Science.gov (United States)

Birckelbaw, Lourdes G.

1992-01-01

A ski jump model was developed to predict ski jump takeoff performance for a short takeoff and vertical landing (STOVL) aircraft. The objective was to verify the model with results from a piloted simulation of a mixed flow, remote lift STOVL aircraft. The prediction model is discussed. The predicted results are compared with the piloted simulation results. The ski jump model can be utilized for basic research of other thrust vectoring STOVL aircraft performing a ski jump takeoff.

The Search Performance Evaluation and Prediction in Exploratory Search

OpenAIRE

LIU, FEI

2016-01-01

The exploratory search for complex search tasks requires an effective search behavior model to evaluate and predict user search performance. Few studies have investigated the relationship between user search behavior and search performance in exploratory search. This research adopts a mixed approach combining search system development, user search experiment, search query log analysis, and multivariate regression analysis to resolve the knowledge gap. Through this study, it is shown that expl...

Predictive Bias and Sensitivity in NRC Fuel Performance Codes

Energy Technology Data Exchange (ETDEWEB)

Geelhood, Kenneth J.; Luscher, Walter G.; Senor, David J.; Cunningham, Mitchel E.; Lanning, Donald D.; Adkins, Harold E.

2009-10-01

The latest versions of the fuel performance codes, FRAPCON-3 and FRAPTRAN were examined to determine if the codes are intrinsically conservative. Each individual model and type of code prediction was examined and compared to the data that was used to develop the model. In addition, a brief literature search was performed to determine if more recent data have become available since the original model development for model comparison.

Prediction of SFL Interruption Performance from the Results of Arc Simulation during High-Current Phase

Science.gov (United States)

Lee, Jong-Chul; Lee, Won-Ho; Kim, Woun-Jea

2015-09-01

The design and development procedures of SF6 gas circuit breakers are still largely based on trial and error through testing although the development costs go higher every year. The computation cannot cover the testing satisfactorily because all the real processes arc not taken into account. But the knowledge of the arc behavior and the prediction of the thermal-flow inside the interrupters by numerical simulations are more useful than those by experiments due to the difficulties to obtain physical quantities experimentally and the reduction of computational costs in recent years. In this paper, in order to get further information into the interruption process of a SF6 self-blast interrupter, which is based on a combination of thermal expansion and the arc rotation principle, gas flow simulations with a CFD-arc modeling are performed during the whole switching process such as high-current period, pre-current zero period, and current-zero period. Through the complete work, the pressure-rise and the ramp of the pressure inside the chamber before current zero as well as the post-arc current after current zero should be a good criterion to predict the short-line fault interruption performance of interrupters.

Predicting Story Goodness Performance from Cognitive Measures Following Traumatic Brain Injury

Science.gov (United States)

Le, Karen; Coelho, Carl; Mozeiko, Jennifer; Krueger, Frank; Grafman, Jordan

2012-01-01

Purpose: This study examined the prediction of performance on measures of the Story Goodness Index (SGI; Le, Coelho, Mozeiko, & Grafman, 2011) from executive function (EF) and memory measures following traumatic brain injury (TBI). It was hypothesized that EF and memory measures would significantly predict SGI outcomes. Method: One hundred…

Performance Driven Design Systems In Practice

OpenAIRE

Joyce, Sam

2015-01-01

This thesis is concerned with the application of computation in the context of professional architectural practice and specifically towards defining complex buildingsthat are highly integrated with respect to design and engineering performance.The thesis represents applied research undertaken whilst in practice at Foster + Partners.It reviews the current state of the art of computational design techniques to quickly but flexibly model and analyse building options. The application of parametri...

Cognitive load predicts point-of-care ultrasound simulator performance.

Science.gov (United States)

Aldekhyl, Sara; Cavalcanti, Rodrigo B; Naismith, Laura M

2018-02-01

The ability to maintain good performance with low cognitive load is an important marker of expertise. Incorporating cognitive load measurements in the context of simulation training may help to inform judgements of competence. This exploratory study investigated relationships between demographic markers of expertise, cognitive load measures, and simulator performance in the context of point-of-care ultrasonography. Twenty-nine medical trainees and clinicians at the University of Toronto with a range of clinical ultrasound experience were recruited. Participants answered a demographic questionnaire then used an ultrasound simulator to perform targeted scanning tasks based on clinical vignettes. Participants were scored on their ability to both acquire and interpret ultrasound images. Cognitive load measures included participant self-report, eye-based physiological indices, and behavioural measures. Data were analyzed using a multilevel linear modelling approach, wherein observations were clustered by participants. Experienced participants outperformed novice participants on ultrasound image acquisition. Ultrasound image interpretation was comparable between the two groups. Ultrasound image acquisition performance was predicted by level of training, prior ultrasound training, and cognitive load. There was significant convergence between cognitive load measurement techniques. A marginal model of ultrasound image acquisition performance including prior ultrasound training and cognitive load as fixed effects provided the best overall fit for the observed data. In this proof-of-principle study, the combination of demographic and cognitive load measures provided more sensitive metrics to predict ultrasound simulator performance. Performance assessments which include cognitive load can help differentiate between levels of expertise in simulation environments, and may serve as better predictors of skill transfer to clinical practice.