Evaluating the design and reporting of pragmatic trials in osteoarthritis research.

Science.gov (United States)

Ali, Shabana Amanda; Kloseck, Marita; Lee, Karen; Walsh, Kathleen Ellen; MacDermid, Joy C; Fitzsimmons, Deborah

2018-01-01

Among the challenges in health research is translating interventions from controlled experimental settings to clinical and community settings where chronic disease is managed daily. Pragmatic trials offer a method for testing interventions in real-world settings but are seldom used in OA research. The aim of this study was to evaluate the literature on pragmatic trials in OA research up to August 2016 in order to identify strengths and weaknesses in the design and reporting of these trials. We used established guidelines to assess the degree to which 61 OA studies complied with pragmatic trial design and reporting. We assessed design according to the pragmatic-explanatory continuum indicator summary and reporting according to the pragmatic trials extension of the CONsolidated Standards of Reporting Trials guidelines. None of the pragmatic trials met all 11 criteria evaluated and most of the trials met between 5 and 8 of the criteria. Criteria most often unmet pertained to practitioner expertise (by requiring specialists) and criteria most often met pertained to primary outcome analysis (by using intention-to-treat analysis). Our results suggest a lack of highly pragmatic trials in OA research. We identify this as a point of opportunity to improve research translation, since optimizing the design and reporting of pragmatic trials can facilitate implementation of evidence-based interventions for OA care. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Statistical controversies in clinical research: requiem for the 3 + 3 design for phase I trials.

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Paoletti, X; Ezzalfani, M; Le Tourneau, C

2015-09-01

More than 95% of published phase I trials have used the 3 + 3 design to identify the dose to be recommended for phase II trials. However, the statistical community agrees on the limitations of the 3 + 3 design compared with model-based approaches. Moreover, the mechanisms of action of targeted agents strongly challenge the hypothesis that the maximum tolerated dose constitutes the optimal dose, and more outcomes including clinical and biological activity increasingly need to be taken into account to identify the optimal dose. We review key elements from clinical publications and from the statistical literature to show that the 3 + 3 design lacks the necessary flexibility to address the challenges of targeted agents. The design issues raised by expansion cohorts, new definitions of dose-limiting toxicity and trials of combinations are not easily addressed by the 3 + 3 design or its extensions. Alternative statistical proposals have been developed to make a better use of the complex data generated by phase I trials. Their applications require a close collaboration between all actors of early phase clinical trials. © The Author 2015. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Mechanical Design Optimization Using Advanced Optimization Techniques

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Rao, R Venkata

2012-01-01

Mechanical design includes an optimization process in which designers always consider objectives such as strength, deflection, weight, wear, corrosion, etc. depending on the requirements. However, design optimization for a complete mechanical assembly leads to a complicated objective function with a large number of design variables. It is a good practice to apply optimization techniques for individual components or intermediate assemblies than a complete assembly. Analytical or numerical methods for calculating the extreme values of a function may perform well in many practical cases, but may fail in more complex design situations. In real design problems, the number of design parameters can be very large and their influence on the value to be optimized (the goal function) can be very complicated, having nonlinear character. In these complex cases, advanced optimization algorithms offer solutions to the problems, because they find a solution near to the global optimum within reasonable time and computational ...

The REVAMP trial to evaluate HIV resistance testing in sub-Saharan Africa: a case study in clinical trial design in resource limited settings to optimize effectiveness and cost effectiveness estimates.

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Siedner, Mark J; Bwana, Mwebesa B; Moosa, Mahomed-Yunus S; Paul, Michelle; Pillay, Selvan; McCluskey, Suzanne; Aturinda, Isaac; Ard, Kevin; Muyindike, Winnie; Moodley, Pravikrishnen; Brijkumar, Jaysingh; Rautenberg, Tamlyn; George, Gavin; Johnson, Brent; Gandhi, Rajesh T; Sunpath, Henry; Marconi, Vincent C

2017-07-01

In sub-Saharan Africa, rates of sustained HIV virologic suppression remain below international goals. HIV resistance testing, while common in resource-rich settings, has not gained traction due to concerns about cost and sustainability. We designed a randomized clinical trial to determine the feasibility, effectiveness, and cost-effectiveness of routine HIV resistance testing in sub-Saharan Africa. We describe challenges common to intervention studies in resource-limited settings, and strategies used to address them, including: (1) optimizing generalizability and cost-effectiveness estimates to promote transition from study results to policy; (2) minimizing bias due to patient attrition; and (3) addressing ethical issues related to enrollment of pregnant women. The study randomizes people in Uganda and South Africa with virologic failure on first-line therapy to standard of care virologic monitoring or immediate resistance testing. To strengthen external validity, study procedures are conducted within publicly supported laboratory and clinical facilities using local staff. To optimize cost estimates, we collect primary data on quality of life and medical resource utilization. To minimize losses from observation, we collect locally relevant contact information, including Whatsapp account details, for field-based tracking of missing participants. Finally, pregnant women are followed with an adapted protocol which includes an increased visit frequency to minimize risk to them and their fetuses. REVAMP is a pragammatic randomized clinical trial designed to test the effectiveness and cost-effectiveness of HIV resistance testing versus standard of care in sub-Saharan Africa. We anticipate the results will directly inform HIV policy in sub-Saharan Africa to optimize care for HIV-infected patients.

Design of Phase I Combination Trials: Recommendations of the Clinical Trial Design Task Force of the NCI Investigational Drug Steering Committee

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Paller, Channing J.; Bradbury, Penelope A.; Ivy, S. Percy; Seymour, Lesley; LoRusso, Patricia M.; Baker, Laurence; Rubinstein, Larry; Huang, Erich; Collyar, Deborah; Groshen, Susan; Reeves, Steven; Ellis, Lee M.; Sargent, Daniel J.; Rosner, Gary L.; LeBlanc, Michael L.; Ratain, Mark J.

2014-01-01

Anticancer drugs are combined in an effort to treat a heterogeneous tumor or to maximize the pharmacodynamic effect. The development of combination regimens, while desirable, poses unique challenges. These include the selection of agents for combination therapy that may lead to improved efficacy while maintaining acceptable toxicity, the design of clinical trials that provide informative results for individual agents and combinations, and logistical and regulatory challenges. The phase 1 trial is often the initial step in the clinical evaluation of a combination regimen. In view of the importance of combination regimens and the challenges associated with developing them, the Clinical Trial Design (CTD) Task Force of the National Cancer Institute (NCI) Investigational Drug Steering Committee developed a set of recommendations for the phase 1 development of a combination regimen. The first two recommendations focus on the scientific rationale and development plans for the combination regimen; subsequent recommendations encompass clinical design aspects. The CTD Task Force recommends that selection of the proposed regimens be based on a biological or pharmacological rationale supported by clinical and/or robust and validated preclinical evidence, and accompanied by a plan for subsequent development of the combination. The design of the phase 1 clinical trial should take into consideration the potential pharmacokinetic and pharmacodynamic interactions as well as overlapping toxicity. Depending on the specific hypothesized interaction, the primary endpoint may be dose optimization, pharmacokinetics, and/or pharmacodynamic (i.e., biomarker). PMID:25125258

Explanatory Versus Pragmatic Trials: An Essential Concept in Study Design and Interpretation.

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Merali, Zamir; Wilson, Jefferson R

2017-11-01

Randomized clinical trials often represent the highest level of clinical evidence available to evaluate the efficacy of an intervention in clinical medicine. Although the process of randomization serves to maximize internal validity, the external validity, or generalizability, of such studies depends on several factors determined at the design phase of the trial including eligibility criteria, study setting, and outcomes of interest. In general, explanatory trials are optimized to demonstrate the efficacy of an intervention in a highly selected patient group; however, findings from these studies may not be generalizable to the larger clinical problem. In contrast, pragmatic trials attempt to understand the real-world benefit of an intervention by incorporating design elements that allow for greater generalizability and clinical applicability of study results. In this article we describe the explanatory-pragmatic continuum for clinical trials in greater detail. Further, a well-accepted tool for grading trials on this continuum is described, and applied, to 2 recently published trials pertaining to the surgical management of lumbar degenerative spondylolisthesis.

Comparative study for the design of optimal composite pressure vessels

International Nuclear Information System (INIS)

Butt, A.M.; Haq, S.W.U.

2009-01-01

Composite pressure vessels require special design attention to the dome region because of the varying wind angles generated using the filament winding process. Geometric variations in the dome region cause the fiber to change angels and thickness and hence offer difficulty to acquire a constant stress profile (isotensoid). Therefore a dome contour which allows an isotensoid behavior is the required structure. Two design methods to generate dome profiles for similar dome openings were investigated namely Netting Analysis and Optimal Design method. Both methods assume that loads are carried by the fiber alone (monotropic) ignoring the complete composite behavior. Former method produced a lower dome internal volume and a higher fiber thickness as compared to the later optimal design method when studied against different normalized dome opening radiuses. The optimal dome contour was studied in ANSYS with a trial design. The dome was considered to have transversely isotropic property with a dome contour based on monotropic model. While investigating the dome with non linear large displacement finite element analysis, the dome still exhibited isotensoid behavior with transverse isotropic material assignment. Elliptic integrals were used to generate the optimal dome contours and hence elliptic dome contours were formed which were isotensoid in nature with complete composite representation. (author)

Clinical Trial Design for HIV Prevention Research: Determining Standards of Prevention.

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Dawson, Liza; Zwerski, Sheryl

2015-06-01

This article seeks to advance ethical dialogue on choosing standards of prevention in clinical trials testing improved biomedical prevention methods for HIV. The stakes in this area of research are high, given the continued high rates of infection in many countries and the budget limitations that have constrained efforts to expand treatment for all who are currently HIV-infected. New prevention methods are still needed; at the same time, some existing prevention and treatment interventions have been proven effective but are not yet widely available in the countries where they most urgently needed. The ethical tensions in this field of clinical research are well known and have been the subject of extensive debate. There is no single clinical trial design that can optimize all the ethically important goals and commitments involved in research. Several recent articles have described the current ethical difficulties in designing HIV prevention trials, especially in resource limited settings; however, there is no consensus on how to handle clinical trial design decisions, and existing international ethical guidelines offer conflicting advice. This article acknowledges these deep ethical dilemmas and moves beyond a simple descriptive approach to advance an organized method for considering what clinical trial designs will be ethically acceptable for HIV prevention trials, balancing the relevant criteria and providing justification for specific design decisions. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Early surgery versus optimal current step-up practice for chronic pancreatitis (ESCAPE): design and rationale of a randomized trial.

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Ahmed Ali, Usama; Issa, Yama; Bruno, Marco J; van Goor, Harry; van Santvoort, Hjalmar; Busch, Olivier R C; Dejong, Cornelis H C; Nieuwenhuijs, Vincent B; van Eijck, Casper H; van Dullemen, Hendrik M; Fockens, Paul; Siersema, Peter D; Gouma, Dirk J; van Hooft, Jeanin E; Keulemans, Yolande; Poley, Jan W; Timmer, Robin; Besselink, Marc G; Vleggaar, Frank P; Wilder-Smith, Oliver H; Gooszen, Hein G; Dijkgraaf, Marcel G W; Boermeester, Marja A

2013-03-18

In current practice, patients with chronic pancreatitis undergo surgical intervention in a late stage of the disease, when conservative treatment and endoscopic interventions have failed. Recent evidence suggests that surgical intervention early on in the disease benefits patients in terms of better pain control and preservation of pancreatic function. Therefore, we designed a randomized controlled trial to evaluate the benefits, risks and costs of early surgical intervention compared to the current stepwise practice for chronic pancreatitis. The ESCAPE trial is a randomized controlled, parallel, superiority multicenter trial. Patients with chronic pancreatitis, a dilated pancreatic duct (≥5 mm) and moderate pain and/or frequent flare-ups will be registered and followed monthly as potential candidates for the trial. When a registered patient meets the randomization criteria (i.e. need for opioid analgesics) the patient will be randomized to either early surgical intervention (group A) or optimal current step-up practice (group B). An expert panel of chronic pancreatitis specialists will oversee the assessment of eligibility and ensure that allocation to either treatment arm is possible. Patients in group A will undergo pancreaticojejunostomy or a Frey-procedure in case of an enlarged pancreatic head (≥4 cm). Patients in group B will undergo a step-up practice of optimal medical treatment, if needed followed by endoscopic interventions, and if needed followed by surgery, according to predefined criteria. Primary outcome is pain assessed with the Izbicki pain score during a follow-up of 18 months. Secondary outcomes include complications, mortality, total direct and indirect costs, quality of life, pancreatic insufficiency, alternative pain scales, length of hospital admission, number of interventions and pancreatitis flare-ups. For the sample size calculation we defined a minimal clinically relevant difference in the primary endpoint as a difference of at least

Genotype by environment interaction in sunflower (Helianthus annus L.) to optimize trial network efficiency

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Gonzalez-Barrios, P.; Castro, M.; Pérez, O.; Vilaró, D.; Gutiérrez, L.

2017-07-01

Modeling genotype by environment interaction (GEI) is one of the most challenging aspects of plant breeding programs. The use of efficient trial networks is an effective way to evaluate GEI to define selection strategies. Furthermore, the experimental design and the number of locations, replications, and years are crucial aspects of multi-environment trial (MET) network optimization. The objective of this study was to evaluate the efficiency and performance of a MET network of sunflower (Helianthus annuus L.). Specifically, we evaluated GEI in the network by delineating mega-environments, estimating genotypic stability and identifying relevant environmental covariates. Additionally, we optimized the network by comparing experimental design efficiencies. We used the National Evaluation Network of Sunflower Cultivars of Uruguay (NENSU) in a period of 20 years. MET plot yield and flowering time information was used to evaluate GEI. Additionally, meteorological information was studied for each sunflower physiological stage. An optimal network under these conditions should have three replications, two years of evaluation and at least three locations. The use of incomplete randomized block experimental design showed reasonable performance. Three mega-environments were defined, explained mainly by different management of sowing dates. Late sowings dates had the worst performance in grain yield and oil production, associated with higher temperatures before anthesis and fewer days allocated to grain filling. The optimization of MET networks through the analysis of the experimental design efficiency, the presence of GEI, and appropriate management strategies have a positive impact on the expression of yield potential and selection of superior cultivars.

A logical approach to optimize the nanostructured lipid carrier system of irinotecan: efficient hybrid design methodology

International Nuclear Information System (INIS)

Negi, Lalit Mohan; Talegaonkar, Sushama; Jaggi, Manu

2013-01-01

Development of an effective formulation involves careful optimization of a number of excipient and process variables. Sometimes the number of variables is so large that even the most efficient optimization designs require a very large number of trials which put stress on costs as well as time. A creative combination of a number of design methods leads to a smaller number of trials. This study was aimed at the development of nanostructured lipid carriers (NLCs) by using a combination of different optimization methods. A total of 11 variables were first screened using the Plackett–Burman design for their effects on formulation characteristics like size and entrapment efficiency. Four out of 11 variables were found to have insignificant effects on the formulation parameters and hence were screened out. Out of the remaining seven variables, four (concentration of tween-80, lecithin, sodium taurocholate, and total lipid) were found to have significant effects on the size of the particles while the other three (phase ratio, drug to lipid ratio, and sonication time) had a higher influence on the entrapment efficiency. The first four variables were optimized for their effect on size using the Taguchi L9 orthogonal array. The optimized values of the surfactants and lipids were kept constant for the next stage, where the sonication time, phase ratio, and drug:lipid ratio were varied using the Box–Behnken design response surface method to optimize the entrapment efficiency. Finally, by performing only 38 trials, we have optimized 11 variables for the development of NLCs with a size of 143.52 ± 1.2 nm, zeta potential of −32.6 ± 0.54 mV, and 98.22 ± 2.06% entrapment efficiency. (paper)

A statistical approach to optimizing concrete mixture design.

Science.gov (United States)

Ahmad, Shamsad; Alghamdi, Saeid A

2014-01-01

A step-by-step statistical approach is proposed to obtain optimum proportioning of concrete mixtures using the data obtained through a statistically planned experimental program. The utility of the proposed approach for optimizing the design of concrete mixture is illustrated considering a typical case in which trial mixtures were considered according to a full factorial experiment design involving three factors and their three levels (3(3)). A total of 27 concrete mixtures with three replicates (81 specimens) were considered by varying the levels of key factors affecting compressive strength of concrete, namely, water/cementitious materials ratio (0.38, 0.43, and 0.48), cementitious materials content (350, 375, and 400 kg/m(3)), and fine/total aggregate ratio (0.35, 0.40, and 0.45). The experimental data were utilized to carry out analysis of variance (ANOVA) and to develop a polynomial regression model for compressive strength in terms of the three design factors considered in this study. The developed statistical model was used to show how optimization of concrete mixtures can be carried out with different possible options.

A Statistical Approach to Optimizing Concrete Mixture Design

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Shamsad Ahmad

2014-01-01

Full Text Available A step-by-step statistical approach is proposed to obtain optimum proportioning of concrete mixtures using the data obtained through a statistically planned experimental program. The utility of the proposed approach for optimizing the design of concrete mixture is illustrated considering a typical case in which trial mixtures were considered according to a full factorial experiment design involving three factors and their three levels (33. A total of 27 concrete mixtures with three replicates (81 specimens were considered by varying the levels of key factors affecting compressive strength of concrete, namely, water/cementitious materials ratio (0.38, 0.43, and 0.48, cementitious materials content (350, 375, and 400 kg/m3, and fine/total aggregate ratio (0.35, 0.40, and 0.45. The experimental data were utilized to carry out analysis of variance (ANOVA and to develop a polynomial regression model for compressive strength in terms of the three design factors considered in this study. The developed statistical model was used to show how optimization of concrete mixtures can be carried out with different possible options.

Using simulation to aid trial design: Ring-vaccination trials.

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Matt David Thomas Hitchings

2017-03-01

Full Text Available The 2014-6 West African Ebola epidemic highlights the need for rigorous, rapid clinical trial methods for vaccines. A challenge for trial design is making sample size calculations based on incidence within the trial, total vaccine effect, and intracluster correlation, when these parameters are uncertain in the presence of indirect effects of vaccination.We present a stochastic, compartmental model for a ring vaccination trial. After identification of an index case, a ring of contacts is recruited and either vaccinated immediately or after 21 days. The primary outcome of the trial is total vaccine effect, counting cases only from a pre-specified window in which the immediate arm is assumed to be fully protected and the delayed arm is not protected. Simulation results are used to calculate necessary sample size and estimated vaccine effect. Under baseline assumptions about vaccine properties, monthly incidence in unvaccinated rings and trial design, a standard sample-size calculation neglecting dynamic effects estimated that 7,100 participants would be needed to achieve 80% power to detect a difference in attack rate between arms, while incorporating dynamic considerations in the model increased the estimate to 8,900. This approach replaces assumptions about parameters at the ring level with assumptions about disease dynamics and vaccine characteristics at the individual level, so within this framework we were able to describe the sensitivity of the trial power and estimated effect to various parameters. We found that both of these quantities are sensitive to properties of the vaccine, to setting-specific parameters over which investigators have little control, and to parameters that are determined by the study design.Incorporating simulation into the trial design process can improve robustness of sample size calculations. For this specific trial design, vaccine effectiveness depends on properties of the ring vaccination design and on the

SPIRIT: A seamless phase I/II randomized design for immunotherapy trials.

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Guo, Beibei; Li, Daniel; Yuan, Ying

2018-06-07

Immunotherapy-treatments that enlist the immune system to battle tumors-has received widespread attention in cancer research. Due to its unique features and mechanisms for treating cancer, immunotherapy requires novel clinical trial designs. We propose a Bayesian seamless phase I/II randomized design for immunotherapy trials (SPIRIT) to find the optimal biological dose (OBD) defined in terms of the restricted mean survival time. We jointly model progression-free survival and the immune response. Progression-free survival is used as the primary endpoint to determine the OBD, and the immune response is used as an ancillary endpoint to quickly screen out futile doses. Toxicity is monitored throughout the trial. The design consists of two seamlessly connected stages. The first stage identifies a set of safe doses. The second stage adaptively randomizes patients to the safe doses identified and uses their progression-free survival and immune response to find the OBD. The simulation study shows that the SPIRIT has desirable operating characteristics and outperforms the conventional design. Copyright © 2018 John Wiley & Sons, Ltd.

Design of clinical trials Phase I and II with radiopharmaceuticals

International Nuclear Information System (INIS)

Giannone, C.A.; Soroa, V.E.

2015-01-01

We presented some usual designs for clinical studies in Phase I and Phase II. For Phase I we considered the 3 + 3 Classic design, designs with accelerated titration and those with dose escalation schemes with overdose control (EWOC). For Phase II designs with efficacy outcomes are presented. The design proposed by Fleming is discussed as well as those with inclusion of patients in two stages: Gehan’s design and the Optimal two–stage Simon’s design. We also discussed the design of combined endpoints of efficacy and safety of Bryant and Day with an application example of therapeutically Lu-177. Finally some proposals for phase II trials with control group are considered. (authors) [es

Sequential, Multiple Assignment, Randomized Trial Designs in Immuno-oncology Research.

Science.gov (United States)

Kidwell, Kelley M; Postow, Michael A; Panageas, Katherine S

2018-02-15

Clinical trials investigating immune checkpoint inhibitors have led to the approval of anti-CTLA-4 (cytotoxic T-lymphocyte antigen-4), anti-PD-1 (programmed death-1), and anti-PD-L1 (PD-ligand 1) drugs by the FDA for numerous tumor types. In the treatment of metastatic melanoma, combinations of checkpoint inhibitors are more effective than single-agent inhibitors, but combination immunotherapy is associated with increased frequency and severity of toxicity. There are questions about the use of combination immunotherapy or single-agent anti-PD-1 as initial therapy and the number of doses of either approach required to sustain a response. In this article, we describe a novel use of sequential, multiple assignment, randomized trial (SMART) design to evaluate immune checkpoint inhibitors to find treatment regimens that adapt within an individual based on intermediate response and lead to the longest overall survival. We provide a hypothetical example SMART design for BRAF wild-type metastatic melanoma as a framework for investigating immunotherapy treatment regimens. We compare implementing a SMART design to implementing multiple traditional randomized clinical trials. We illustrate the benefits of a SMART over traditional trial designs and acknowledge the complexity of a SMART. SMART designs may be an optimal way to find treatment strategies that yield durable response, longer survival, and lower toxicity. Clin Cancer Res; 24(4); 730-6. ©2017 AACR . ©2017 American Association for Cancer Research.

Sequential ensemble-based optimal design for parameter estimation: SEQUENTIAL ENSEMBLE-BASED OPTIMAL DESIGN

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Man, Jun [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Zhang, Jiangjiang [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Li, Weixuan [Pacific Northwest National Laboratory, Richland Washington USA; Zeng, Lingzao [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Wu, Laosheng [Department of Environmental Sciences, University of California, Riverside California USA

2016-10-01

The ensemble Kalman filter (EnKF) has been widely used in parameter estimation for hydrological models. The focus of most previous studies was to develop more efficient analysis (estimation) algorithms. On the other hand, it is intuitively understandable that a well-designed sampling (data-collection) strategy should provide more informative measurements and subsequently improve the parameter estimation. In this work, a Sequential Ensemble-based Optimal Design (SEOD) method, coupled with EnKF, information theory and sequential optimal design, is proposed to improve the performance of parameter estimation. Based on the first-order and second-order statistics, different information metrics including the Shannon entropy difference (SD), degrees of freedom for signal (DFS) and relative entropy (RE) are used to design the optimal sampling strategy, respectively. The effectiveness of the proposed method is illustrated by synthetic one-dimensional and two-dimensional unsaturated flow case studies. It is shown that the designed sampling strategies can provide more accurate parameter estimation and state prediction compared with conventional sampling strategies. Optimal sampling designs based on various information metrics perform similarly in our cases. The effect of ensemble size on the optimal design is also investigated. Overall, larger ensemble size improves the parameter estimation and convergence of optimal sampling strategy. Although the proposed method is applied to unsaturated flow problems in this study, it can be equally applied in any other hydrological problems.

Design and protocol for the Dialysis Optimal Health Program (DOHP) randomised controlled trial.

Science.gov (United States)

Knowles, Simon R; Ski, Chantal F; Langham, Robyn; O'Flaherty, Emmet; Thompson, David R; Rossell, Susan L; Moore, Gaye; Hsueh, Ya-Seng Arthur; Castle, David J

2016-09-09

Chronic kidney disease (CKD) and end-stage kidney disease (ESKD) are serious and growing health problems with enormous impact on psychological and social functioning. Despite high rates of comorbid depression and anxiety in these patient populations, and the adverse impact these have upon treatment adherence, quality of life, social connectedness and healthcare costs there has been little attention focused on the prevention or management of these problems. Thus, our aim was to evaluate the Dialysis Optimal Health Program (DOHP) that adopts a person-centred approach and engages collaborative therapy to educate and support those diagnosed with ESKD who are commencing dialysis. The study design is a randomised controlled trial. Ninety-six adult patients initiating haemodialysis or peritoneal dialysis will be randomly allocated to either the intervention (DOHP) or usual care group. Participants receiving the intervention will receive nine (8 + 1 booster session) sequential sessions based on a structured information/workbook, psychosocial and educational supports and skills building. The primary outcome measures are depression and anxiety (assessed by the Hospital Anxiety and Depression Scale; HADS). Secondary outcomes include health-related quality of life (assessed by the Kidney Disease Quality of Life instrument; KDQOL), self-efficacy (assessed by General Self-Efficacy Scale) and clinical indices (e.g. albumin and haemoglobin levels). Cost-effectiveness analysis and process evaluation will also be performed to assess the economic value and efficacy of the DOHP. Primary and secondary measures will be collected at baseline and at 3-, 6-, and 12-month follow-up time points. We believe that this innovative trial will enhance knowledge of interventions aimed at supporting patients in the process of starting dialysis, and will broaden the focus from physical symptoms to include psychosocial factors such as depression, anxiety, self-efficacy, wellbeing and community

Modeling and Design of Capacitive Micromachined Ultrasonic Transducers Based-on Database Optimization

International Nuclear Information System (INIS)

Chang, M W; Gwo, T J; Deng, T M; Chang, H C

2006-01-01

A Capacitive Micromachined Ultrasonic Transducers simulation database, based on electromechanical coupling theory, has been fully developed for versatile capacitive microtransducer design and analysis. Both arithmetic and graphic configurations are used to find optimal parameters based on serial coupling simulations. The key modeling parameters identified can improve microtransducer's character and reliability effectively. This method could be used to reduce design time and fabrication cost, eliminating trial-and-error procedures. Various microtransducers, with optimized characteristics, can be developed economically using the developed database. A simulation to design an ultrasonic microtransducer is completed as an executed example. The dependent relationship between membrane geometry, vibration displacement and output response is demonstrated. The electromechanical coupling effects, mechanical impedance and frequency response are also taken into consideration for optimal microstructures. The microdevice parameters with the best output signal response are predicted, and microfabrication processing constraints and realities are also taken into consideration

Adaptive designs in clinical trials

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Suresh Bowalekar

2011-01-01

Full Text Available In addition to the expensive and lengthy process of developing a new medicine, the attrition rate in clinical research was on the rise, resulting in stagnation in the development of new compounds. As a consequence to this, the US Food and Drug Administration released a critical path initiative document in 2004, highlighting the need for developing innovative trial designs. One of the innovations suggested the use of adaptive designs for clinical trials. Thus, post critical path initiative, there is a growing interest in using adaptive designs for the development of pharmaceutical products. Adaptive designs are expected to have great potential to reduce the number of patients and duration of trial and to have relatively less exposure to new drug. Adaptive designs are not new in the sense that the task of interim analysis (IA/review of the accumulated data used in adaptive designs existed in the past too. However, such reviews/analyses of accumulated data were not necessarily planned at the stage of planning clinical trial and the methods used were not necessarily compliant with clinical trial process. The Bayesian approach commonly used in adaptive designs was developed by Thomas Bayes in the 18th century, about hundred years prior to the development of modern statistical methods by the father of modern statistics, Sir Ronald A. Fisher, but the complexity involved in Bayesian approach prevented its use in real life practice. The advances in the field of computer and information technology over the last three to four decades has changed the scenario and the Bayesian techniques are being used in adaptive designs in addition to other sequential methods used in IA. This paper attempts to describe the various adaptive designs in clinical trial and views of stakeholders about feasibility of using them, without going into mathematical complexities.

Adaptive designs in clinical trials.

Science.gov (United States)

Bowalekar, Suresh

2011-01-01

In addition to the expensive and lengthy process of developing a new medicine, the attrition rate in clinical research was on the rise, resulting in stagnation in the development of new compounds. As a consequence to this, the US Food and Drug Administration released a critical path initiative document in 2004, highlighting the need for developing innovative trial designs. One of the innovations suggested the use of adaptive designs for clinical trials. Thus, post critical path initiative, there is a growing interest in using adaptive designs for the development of pharmaceutical products. Adaptive designs are expected to have great potential to reduce the number of patients and duration of trial and to have relatively less exposure to new drug. Adaptive designs are not new in the sense that the task of interim analysis (IA)/review of the accumulated data used in adaptive designs existed in the past too. However, such reviews/analyses of accumulated data were not necessarily planned at the stage of planning clinical trial and the methods used were not necessarily compliant with clinical trial process. The Bayesian approach commonly used in adaptive designs was developed by Thomas Bayes in the 18th century, about hundred years prior to the development of modern statistical methods by the father of modern statistics, Sir Ronald A. Fisher, but the complexity involved in Bayesian approach prevented its use in real life practice. The advances in the field of computer and information technology over the last three to four decades has changed the scenario and the Bayesian techniques are being used in adaptive designs in addition to other sequential methods used in IA. This paper attempts to describe the various adaptive designs in clinical trial and views of stakeholders about feasibility of using them, without going into mathematical complexities.

Design of Phase II Non-inferiority Trials.

Science.gov (United States)

Jung, Sin-Ho

2017-09-01

With the development of inexpensive treatment regimens and less invasive surgical procedures, we are confronted with non-inferiority study objectives. A non-inferiority phase III trial requires a roughly four times larger sample size than that of a similar standard superiority trial. Because of the large required sample size, we often face feasibility issues to open a non-inferiority trial. Furthermore, due to lack of phase II non-inferiority trial design methods, we do not have an opportunity to investigate the efficacy of the experimental therapy through a phase II trial. As a result, we often fail to open a non-inferiority phase III trial and a large number of non-inferiority clinical questions still remain unanswered. In this paper, we want to develop some designs for non-inferiority randomized phase II trials with feasible sample sizes. At first, we review a design method for non-inferiority phase III trials. Subsequently, we propose three different designs for non-inferiority phase II trials that can be used under different settings. Each method is demonstrated with examples. Each of the proposed design methods is shown to require a reasonable sample size for non-inferiority phase II trials. The three different non-inferiority phase II trial designs are used under different settings, but require similar sample sizes that are typical for phase II trials.

Optimization Design of Multi-Parameters in Rail Launcher System

Directory of Open Access Journals (Sweden)

Yujiao Zhang

2014-05-01

Full Text Available Today the energy storage systems are still encumbering, therefore it is useful to think about the optimization of a railgun system in order to achieve the best performance with the lowest energy input. In this paper, an optimal design method considering 5 parameters is proposed to improve the energy conversion efficiency of a simple railgun. In order to avoid costly trials, the field- circuit method is employed to analyze the operations of different structural railguns with different parameters respectively. And the orthogonal test approach is used to guide the simulation for choosing the better parameter combinations, as well reduce the calculation cost. The research shows that the proposed method gives a better result in the energy efficiency of the system. To improve the energy conversion efficiency of electromagnetic rail launchers, the selection of more parameters must be considered in the design stage, such as the width, height and length of rail, the distance between rail pair, and pulse forming inductance. However, the relationship between these parameters and energy conversion efficiency cannot be directly described by one mathematical expression. So optimization methods must be applied to conduct design. In this paper, a rail launcher with five parameters was optimized by using orthogonal test method. According to the arrangement of orthogonal table, the better parameters’ combination can be obtained through less calculation. Under the condition of different parameters’ value, field and circuit simulation analysis were made. The results show that the energy conversion efficiency of the system is increased by 71.9 % after parameters optimization.

Design of the BRISC study: a multicentre controlled clinical trial to optimize the communication of breast cancer risks in genetic counselling

Directory of Open Access Journals (Sweden)

Menko Fred H

2008-10-01

Full Text Available Abstract Background Understanding risks is considered to be crucial for informed decision-making. Inaccurate risk perception is a common finding in women with a family history of breast cancer attending genetic counseling. As yet, it is unclear how risks should best be communicated in clinical practice. This study protocol describes the design and methods of the BRISC (Breast cancer RISk Communication study evaluating the effect of different formats of risk communication on the counsellee's risk perception, psychological well-being and decision-making regarding preventive options for breast cancer. Methods and design The BRISC study is designed as a pre-post-test controlled group intervention trial with repeated measurements using questionnaires. The intervention-an additional risk consultation-consists of one of 5 conditions that differ in the way counsellee's breast cancer risk is communicated: 1 lifetime risk in numerical format (natural frequencies, i.e. X out of 100, 2 lifetime risk in both numerical format and graphical format (population figures, 3 lifetime risk and age-related risk in numerical format, 4 lifetime risk and age-related risk in both numerical format and graphical format, and 5 lifetime risk in percentages. Condition 6 is the control condition in which no intervention is given (usual care. Participants are unaffected women with a family history of breast cancer attending one of three participating clinical genetic centres in the Netherlands. Discussion The BRISC study allows for an evaluation of the effects of different formats of communicating breast cancer risks to counsellees. The results can be used to optimize risk communication in order to improve informed decision-making among women with a family history of breast cancer. They may also be useful for risk communication in other health-related services. Trial registration Current Controlled Trials ISRCTN14566836.

Rotorcraft Optimization Tools: Incorporating Rotorcraft Design Codes into Multi-Disciplinary Design, Analysis, and Optimization

Science.gov (United States)

Meyn, Larry A.

2018-01-01

One of the goals of NASA's Revolutionary Vertical Lift Technology Project (RVLT) is to provide validated tools for multidisciplinary design, analysis and optimization (MDAO) of vertical lift vehicles. As part of this effort, the software package, RotorCraft Optimization Tools (RCOTOOLS), is being developed to facilitate incorporating key rotorcraft conceptual design codes into optimizations using the OpenMDAO multi-disciplinary optimization framework written in Python. RCOTOOLS, also written in Python, currently supports the incorporation of the NASA Design and Analysis of RotorCraft (NDARC) vehicle sizing tool and the Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics II (CAMRAD II) analysis tool into OpenMDAO-driven optimizations. Both of these tools use detailed, file-based inputs and outputs, so RCOTOOLS provides software wrappers to update input files with new design variable values, execute these codes and then extract specific response variable values from the file outputs. These wrappers are designed to be flexible and easy to use. RCOTOOLS also provides several utilities to aid in optimization model development, including Graphical User Interface (GUI) tools for browsing input and output files in order to identify text strings that are used to identify specific variables as optimization input and response variables. This paper provides an overview of RCOTOOLS and its use

Reinventing clinical trials: a review of innovative biomarker trial designs in cancer therapies.

Science.gov (United States)

Lin, Ja-An; He, Pei

2015-06-01

Recently, new clinical trial designs involving biomarkers have been studied and proposed in cancer clinical research, in the hope of incorporating the rapid growing basic research into clinical practices. Journal articles related to various biomarkers and their role in cancer clinical trial, articles and books about statistical issues in trial design, and regulatory website, documents, and guidance for submission of targeted cancer therapies. The drug development process involves four phases. The confirmatory Phase III is essential in regulatory approval of a special treatment. Regulatory agency has restrictions on confirmatory trials 'using adaptive designs'. No rule of thumb to pick the most appropriate design for biomarker-related trials. Statistical issues to solve in new designs. Regulatory acceptance of the 'newly proposed trial designs'. Biomarker-related trial designs that can resolve the statistical issues and satisfy the regulatory requirement. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Optimal Network-Topology Design

Science.gov (United States)

Li, Victor O. K.; Yuen, Joseph H.; Hou, Ting-Chao; Lam, Yuen Fung

1987-01-01

Candidate network designs tested for acceptability and cost. Optimal Network Topology Design computer program developed as part of study on topology design and analysis of performance of Space Station Information System (SSIS) network. Uses efficient algorithm to generate candidate network designs consisting of subsets of set of all network components, in increasing order of total costs and checks each design to see whether it forms acceptable network. Technique gives true cost-optimal network and particularly useful when network has many constraints and not too many components. Program written in PASCAL.

Conceptual optimal design of jackets

DEFF Research Database (Denmark)

Sandal, Kasper; Verbart, Alexander; Stolpe, Mathias

Structural optimization can explore a large design space (400 jackets) in a short time (2 hours), and thus lead to better conceptual jacket designs.......Structural optimization can explore a large design space (400 jackets) in a short time (2 hours), and thus lead to better conceptual jacket designs....

Case Example of Dose Optimization Using Data From Bortezomib Dose-Finding Clinical Trials.

Science.gov (United States)

Lee, Shing M; Backenroth, Daniel; Cheung, Ying Kuen Ken; Hershman, Dawn L; Vulih, Diana; Anderson, Barry; Ivy, Percy; Minasian, Lori

2016-04-20

The current dose-finding methodology for estimating the maximum tolerated dose of investigational anticancer agents is based on the cytotoxic chemotherapy paradigm. Molecularly targeted agents (MTAs) have different toxicity profiles, which may lead to more long-lasting mild or moderate toxicities as well as to late-onset and cumulative toxicities. Several approved MTAs have been poorly tolerated during long-term administration, leading to postmarketing dose optimization studies to re-evaluate the optimal treatment dose. Using data from completed bortezomib dose-finding trials, we explore its toxicity profile, optimize its dose, and examine the appropriateness of current designs for identifying an optimal dose. We classified the toxicities captured from 481 patients in 14 bortezomib dose-finding studies conducted through the National Cancer Institute Cancer Therapy Evaluation Program, computed the incidence of late-onset toxicities, and compared the incidence of dose-limiting toxicities (DLTs) among groups of patients receiving different doses of bortezomib. A total of 13,008 toxicities were captured: 46% of patients' first DLTs and 88% of dose reductions or discontinuations of treatment because of toxicity were observed after the first cycle. Moreover, for the approved dose of 1.3 mg/m(2), the estimated cumulative incidence of DLT was > 50%, and the estimated cumulative incidence of dose reduction or treatment discontinuation because of toxicity was nearly 40%. When considering the entire course of treatment, the approved bortezomib dose exceeds the conventional ceiling DLT rate of 20% to 33%. Retrospective analysis of trial data provides an opportunity for dose optimization of MTAs. Future dose-finding studies of MTAs should take into account late-onset toxicities to ensure that a tolerable dose is identified for future efficacy and comparative trials. © 2016 by American Society of Clinical Oncology.

Optimal covariate designs theory and applications

CERN Document Server

Das, Premadhis; Mandal, Nripes Kumar; Sinha, Bikas Kumar

2015-01-01

This book primarily addresses the optimality aspects of covariate designs. A covariate model is a combination of ANOVA and regression models. Optimal estimation of the parameters of the model using a suitable choice of designs is of great importance; as such choices allow experimenters to extract maximum information for the unknown model parameters. The main emphasis of this monograph is to start with an assumed covariate model in combination with some standard ANOVA set-ups such as CRD, RBD, BIBD, GDD, BTIBD, BPEBD, cross-over, multi-factor, split-plot and strip-plot designs, treatment control designs, etc. and discuss the nature and availability of optimal covariate designs. In some situations, optimal estimations of both ANOVA and the regression parameters are provided. Global optimality and D-optimality criteria are mainly used in selecting the design. The standard optimality results of both discrete and continuous set-ups have been adapted, and several novel combinatorial techniques have been applied for...

The DIAN-TU Next Generation Alzheimer’s prevention trial: adaptive design and disease progression model

Science.gov (United States)

Bateman, Randall J.; Benzinger, Tammie L.; Berry, Scott; Clifford, David B.; Duggan, Cynthia; Fagan, Anne M.; Fanning, Kathleen; Farlow, Martin R.; Hassenstab, Jason; McDade, Eric M.; Mills, Susan; Paumier, Katrina; Quintana, Melanie; Salloway, Stephen P.; Santacruz, Anna; Schneider, Lon S.; Wang, Guoqiao; Xiong, Chengjie

2016-01-01

INTRODUCTION The Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU) trial is an adaptive platform trial testing multiple drugs to slow or prevent the progression of Alzheimer’s disease in autosomal dominant Alzheimer’s disease (ADAD) families. With completion of enrollment of the first two drug arms, the DIAN-TU now plans to add new drugs to the platform, designated as the Next Generation Prevention Trial (NexGen). METHODS In collaboration with ADAD families, philanthropic organizations, academic leaders, the DIAN-TU Pharma Consortium, the NIH, and regulatory colleagues, the DIAN-TU developed innovative clinical study designs for the DIAN-TU NexGen trial. RESULTS Our expanded trials toolbox consists of a Disease Progression Model for ADAD, primary endpoint DIAN-TU cognitive performance composite, biomarker development, self-administered cognitive assessments, adaptive dose adjustments, and blinded data collection through the last participant completion. CONCLUSION These steps represent elements to improve efficacy of the adaptive platform trial and a continued effort to optimize prevention and treatment trials in ADAD. PMID:27583651

Design optimization applied in structural dynamics

NARCIS (Netherlands)

Akcay-Perdahcioglu, Didem; de Boer, Andries; van der Hoogt, Peter; Tiskarna, T

2007-01-01

This paper introduces the design optimization strategies, especially for structures which have dynamic constraints. Design optimization involves first the modeling and then the optimization of the problem. Utilizing the Finite Element (FE) model of a structure directly in an optimization process

Optimal Design and Related Areas in Optimization and Statistics

CERN Document Server

Pronzato, Luc

2009-01-01

This edited volume, dedicated to Henry P. Wynn, reflects his broad range of research interests, focusing in particular on the applications of optimal design theory in optimization and statistics. It covers algorithms for constructing optimal experimental designs, general gradient-type algorithms for convex optimization, majorization and stochastic ordering, algebraic statistics, Bayesian networks and nonlinear regression. Written by leading specialists in the field, each chapter contains a survey of the existing literature along with substantial new material. This work will appeal to both the

Flat-plate photovoltaic array design optimization

Science.gov (United States)

Ross, R. G., Jr.

1980-01-01

An analysis is presented which integrates the results of specific studies in the areas of photovoltaic structural design optimization, optimization of array series/parallel circuit design, thermal design optimization, and optimization of environmental protection features. The analysis is based on minimizing the total photovoltaic system life-cycle energy cost including repair and replacement of failed cells and modules. This approach is shown to be a useful technique for array optimization, particularly when time-dependent parameters such as array degradation and maintenance are involved.

Advanced methods for the analysis, design, and optimization of SMA-based aerostructures

International Nuclear Information System (INIS)

Hartl, D J; Lagoudas, D C; Calkins, F T

2011-01-01

Engineers continue to apply shape memory alloys to aerospace actuation applications due to their high energy density, robust solid-state actuation, and silent and shock-free operation. Past design and development of such actuators relied on experimental trial and error and empirically derived graphical methods. Over the last two decades, however, it has been repeatedly demonstrated that existing SMA constitutive models can capture stabilized SMA transformation behaviors with sufficient accuracy. This work builds upon past successes and suggests a general framework by which predictive tools can be used to assess the responses of many possible design configurations in an automated fashion. By applying methods of design optimization, it is shown that the integrated implementation of appropriate analysis tools can guide engineers and designers to the best design configurations. A general design optimization framework is proposed for the consideration of any SMA component or assembly of such components that applies when the set of design variables includes many members. This is accomplished by relying on commercially available software and utilizing tools already well established in the design optimization community. Such tools are combined with finite element analysis (FEA) packages that consider a multitude of structural effects. The foundation of this work is a three-dimensional thermomechanical constitutive model for SMAs applicable for arbitrarily shaped bodies. A reduced-order implementation also allows computationally efficient analysis of structural components such as wires, rods, beams and shells. The use of multiple optimization schemes, the consideration of assembled components, and the accuracy of the implemented constitutive model in full and reduced-order forms are all demonstrated

A surrogate based multistage-multilevel optimization procedure for multidisciplinary design optimization

OpenAIRE

Yao, W.; Chen, X.; Ouyang, Q.; Van Tooren, M.

2011-01-01

Optimization procedure is one of the key techniques to address the computational and organizational complexities of multidisciplinary design optimization (MDO). Motivated by the idea of synthetically exploiting the advantage of multiple existing optimization procedures and meanwhile complying with the general process of satellite system design optimization in conceptual design phase, a multistage-multilevel MDO procedure is proposed in this paper by integrating multiple-discipline-feasible (M...

Optimization of 3D Field Design

Science.gov (United States)

Logan, Nikolas; Zhu, Caoxiang

2017-10-01

Recent progress in 3D tokamak modeling is now leveraged to create a conceptual design of new external 3D field coils for the DIII-D tokamak. Using the IPEC dominant mode as a target spectrum, the Finding Optimized Coils Using Space-curves (FOCUS) code optimizes the currents and 3D geometry of multiple coils to maximize the total set's resonant coupling. The optimized coils are individually distorted in space, creating toroidal ``arrays'' containing a variety of shapes that often wrap around a significant poloidal extent of the machine. The generalized perturbed equilibrium code (GPEC) is used to determine optimally efficient spectra for driving total, core, and edge neoclassical toroidal viscosity (NTV) torque and these too provide targets for the optimization of 3D coil designs. These conceptual designs represent a fundamentally new approach to 3D coil design for tokamaks targeting desired plasma physics phenomena. Optimized coil sets based on plasma response theory will be relevant to designs for future reactors or on any active machine. External coils, in particular, must be optimized for reliable and efficient fusion reactor designs. Work supported by the US Department of Energy under DE-AC02-09CH11466.

Optimal Market Design

NARCIS (Netherlands)

Boone, J.; Goeree, J.K.

2010-01-01

This paper introduces three methodological advances to study the optimal design of static and dynamic markets. First, we apply a mechanism design approach to characterize all incentive-compatible market equilibria. Second, we conduct a normative analysis, i.e. we evaluate alternative competition and

Divertor design through shape optimization

International Nuclear Information System (INIS)

Dekeyser, W.; Baelmans, M.; Reiter, D.

2012-01-01

Due to the conflicting requirements, complex physical processes and large number of design variables, divertor design for next step fusion reactors is a challenging problem, often relying on large numbers of computationally expensive numerical simulations. In this paper, we attempt to partially automate the design process by solving an appropriate shape optimization problem. Design requirements are incorporated in a cost functional which measures the performance of a certain design. By means of changes in the divertor shape, which in turn lead to changes in the plasma state, this cost functional can be minimized. Using advanced adjoint methods, optimal solutions are computed very efficiently. The approach is illustrated by designing divertor targets for optimal power load spreading, using a simplified edge plasma model (copyright 2012 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

ATHENA optimized coating design

DEFF Research Database (Denmark)

Ferreira, Desiree Della Monica; Christensen, Finn Erland; Jakobsen, Anders Clemen

2012-01-01

The optimization of coating design for the ATHENA mission si described and the possibility of increasing the telescope effective area in the range between 0.1 and 10 keV is investigated. An independent computation of the on-axis effective area based on the mirror design of ATHENA is performed...... in order to review the current coating baseline. The performance of several material combinations, considering a simple bi-layer, simple multilayer and linear graded multilayer coatings are tested and simulation of the mirror performance considering both the optimized coating design and the coating...

Spine device clinical trials: design and sponsorship.

Science.gov (United States)

Cher, Daniel J; Capobianco, Robyn A

2015-05-01

Multicenter prospective randomized clinical trials represent the best evidence to support the safety and effectiveness of medical devices. Industry sponsorship of multicenter clinical trials is purported to lead to bias. To determine what proportion of spine device-related trials are industry-sponsored and the effect of industry sponsorship on trial design. Analysis of data from a publicly available clinical trials database. Clinical trials of spine devices registered on ClinicalTrials.gov, a publicly accessible trial database, were evaluated in terms of design, number and location of study centers, and sample size. The relationship between trial design characteristics and study sponsorship was evaluated using logistic regression and general linear models. One thousand six hundred thrity-eight studies were retrieved from ClinicalTrials.gov using the search term "spine." Of the 367 trials that focused on spine surgery, 200 (54.5%) specifically studied devices for spine surgery and 167 (45.5%) focused on other issues related to spine surgery. Compared with nondevice trials, device trials were far more likely to be sponsored by the industry (74% vs. 22.2%, odds ratio (OR) 9.9 [95% confidence interval 6.1-16.3]). Industry-sponsored device trials were more likely multicenter (80% vs. 29%, OR 9.8 [4.8-21.1]) and had approximately four times as many participating study centers (pdevices not sponsored by the industry. Most device-related spine research is industry-sponsored. Multicenter trials are more likely to be industry-sponsored. These findings suggest that previously published studies showing larger effect sizes in industry-sponsored vs. nonindustry-sponsored studies may be biased as a result of failure to take into account the marked differences in design and purpose. Copyright © 2015 Elsevier Inc. All rights reserved.

Research on Multidisciplinary Optimization Design of Bridge Crane

Directory of Open Access Journals (Sweden)

Tong Yifei

2013-01-01

Full Text Available Bridge crane is one of the most widely used cranes in our country, which is indispensable equipment for material conveying in the modern production. In this paper, the framework of multidisciplinary optimization for bridge crane is proposed. The presented research on crane multidisciplinary design technology for energy saving includes three levels, respectively: metal structures level, transmission design level, and electrical system design level. The shape optimal mathematical model of the crane is established for shape optimization design of metal structure level as well as size optimal mathematical model and topology optimal mathematical model of crane for topology optimization design of metal structure level is established. Finally, system-level multidisciplinary energy-saving optimization design of bridge crane is further carried out with energy-saving transmission design results feedback to energy-saving optimization design of metal structure. The optimization results show that structural optimization design can reduce total mass of crane greatly by using the finite element analysis and multidisciplinary optimization technology premised on the design requirements of cranes such as stiffness and strength; thus, energy-saving design can be achieved.

A Systematic Optimization Design Method for Complex Mechatronic Products Design and Development

Directory of Open Access Journals (Sweden)

Jie Jiang

2018-01-01

Full Text Available Designing a complex mechatronic product involves multiple design variables, objectives, constraints, and evaluation criteria as well as their nonlinearly coupled relationships. The design space can be very big consisting of many functional design parameters, structural design parameters, and behavioral design (or running performances parameters. Given a big design space and inexplicit relations among them, how to design a product optimally in an optimization design process is a challenging research problem. In this paper, we propose a systematic optimization design method based on design space reduction and surrogate modelling techniques. This method firstly identifies key design parameters from a very big design space to reduce the design space, secondly uses the identified key design parameters to establish a system surrogate model based on data-driven modelling principles for optimization design, and thirdly utilizes the multiobjective optimization techniques to achieve an optimal design of a product in the reduced design space. This method has been tested with a high-speed train design. With comparison to others, the research results show that this method is practical and useful for optimally designing complex mechatronic products.

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.

Optimal design of marine steam turbine

International Nuclear Information System (INIS)

Liu Chengyang; Yan Changqi; Wang Jianjun

2012-01-01

The marine steam turbine is one of the key equipment in marine power plant, and it tends to using high power steam turbine, which makes the steam turbine to be heavier and larger, it causes difficulties to the design and arrangement of the steam turbine, and the marine maneuverability is seriously influenced. Therefore, it is necessary to apply optimization techniques to the design of the steam turbine in order to achieve the minimum weight or volume by means of finding the optimum combination of design parameters. The math model of the marine steam turbine design calculation was established. The sensitivities of condenser pressure, power ratio of HP turbine with LP turbine, and the ratio of diameter with height at the end stage of LP turbine, which influence the weight of the marine steam turbine, were analyzed. The optimal design of the marine steam turbine, aiming at the weight minimization while satisfying the structure and performance constraints, was carried out with the hybrid particle swarm optimization algorithm. The results show that, steam turbine weight is reduced by 3.13% with the optimization scheme. Finally, the optimization results were analyzed, and the steam turbine optimization design direction was indicated. (authors)

Design Optimization Toolkit: Users' Manual

Energy Technology Data Exchange (ETDEWEB)

Aguilo Valentin, Miguel Alejandro [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Computational Solid Mechanics and Structural Dynamics

2014-07-01

The Design Optimization Toolkit (DOTk) is a stand-alone C++ software package intended to solve complex design optimization problems. DOTk software package provides a range of solution methods that are suited for gradient/nongradient-based optimization, large scale constrained optimization, and topology optimization. DOTk was design to have a flexible user interface to allow easy access to DOTk solution methods from external engineering software packages. This inherent flexibility makes DOTk barely intrusive to other engineering software packages. As part of this inherent flexibility, DOTk software package provides an easy-to-use MATLAB interface that enables users to call DOTk solution methods directly from the MATLAB command window.

Design Optimization of Internal Flow Devices

DEFF Research Database (Denmark)

Madsen, Jens Ingemann

The power of computational fluid dynamics is boosted through the use of automated design optimization methodologies. The thesis considers both derivative-based search optimization and the use of response surface methodologies.......The power of computational fluid dynamics is boosted through the use of automated design optimization methodologies. The thesis considers both derivative-based search optimization and the use of response surface methodologies....

New Methodology for Optimal Flight Control Using Differential Evolution Algorithms Applied on the Cessna Citation X Business Aircraft – Part 1. Design and Optimization

Directory of Open Access Journals (Sweden)

Yamina BOUGHARI

2017-06-01

Full Text Available Setting the appropriate controllers for aircraft stability and control augmentation systems are complicated and time consuming tasks. As in the Linear Quadratic Regulator method gains are found by selecting the appropriate weights or as in the Proportional Integrator Derivative control by tuning gains. A trial and error process is usually employed for the determination of weighting matrices, which is normally a time consuming procedure. Flight Control Law were optimized and designed by combining the Deferential Evolution algorithm, the Linear Quadratic Regulator method, and the Proportional Integral controller. The optimal controllers were used to reach satisfactory aircraft’s dynamic and safe flight operations with respect to the augmentation systems’ handling qualities, and design requirements for different flight conditions. Furthermore the design and the clearance of the controllers over the flight envelope were automated using a Graphical User Interface, which offers to the designer, the flexibility to change the design requirements. In the aim of reducing time, and costs of the Flight Control Law design, one fitness function has been used for both optimizations, and using design requirements as constraints. Consequently the Flight Control Law design process complexity was reduced by using the meta-heuristic algorithm.

Machine learning paradigms in design optimization: Applications in turbine aerodynamic design

Science.gov (United States)

Goel, Sanjay

Mechanisms of incorporating machine learning paradigms in design optimization have been investigated in the current research. The primary focus of the work is on machine learning algorithms which use computational models that are analogous to the hypothesized principles of natural or biological learning. Examples from structural and aerodynamic optimization have been used to demonstrate the potential of the proposed schemes. The first strategy examined in the current work seeks to improve the convergence of optimization problems by pruning the search space of weak variables. Such variables are identified by learning from a database of existing designs using neural networks. By using clustering techniques, different sets of weak variables are identified in different regions of the design space. Parameter sensitivity information obtained in the process of identifying weak variables provides accurate heuristics for formulating design rules. The impact of this methodology on obtaining converged designs has been investigated for a turbine design problem. Optimization results from a three-stage power turbine and an aircraft engine turbine are presented in this thesis. The second scheme is an evolutionary design optimization technique which gets progressively 'smarter' during the optimization process by learning from computed domain knowledge. This technique employs adaptive learning mechanisms (classifiers) which recognize the influence of the design variables on the problem solution and then generalize them to dynamically create or change design rules during optimization. This technique, when applied to a constrained optimization problem, shows progressive improvement in convergence of search, as successive generations of rules evolve by learning from the environment. To investigate this methodology, a truss optimization problem is solved with an objective of minimizing the truss weight subject to stress constraints in the truss members. A distinct convergent trend is

Designing clinical trials to assess antiepileptic drugs as monotherapy : difficulties and solutions.

Science.gov (United States)

Perucca, Emilio

2008-01-01

Designing monotherapy trials in epilepsy is fraught with many hurdles, including diagnostic and classification difficulties, sparse information regarding the natural history of the disorder, and ethical objections to the use of placebo or a suboptimal comparator in a condition where the consequences of therapeutic failure can be serious. These issues are further complicated by regulatory differences between the US and the EU.In the US, the FDA considers that evidence of efficacy requires demonstration of superiority to a comparator. Because available antiepileptic drugs possess relatively high efficacy, in most settings it is unrealistic to expect that a new treatment will be superior to a standard treatment used at optimized dosages. To circumvent this problem, trial designs have been developed whereby patients in the control group are assigned to receive a suboptimal comparator and are required to exit from the trial if seizure deterioration occurs. This allows demonstration of a between-group difference in efficacy endpoints, such as time to exit or time to first seizure. Although these trials have come under increasing criticism because of ethical concerns, extensive information is now available on the outcome of patients with chronic epilepsy randomized to suboptimal treatment in similarly designed conversion to monotherapy trials. This has allowed the construction of a dataset of historical controls against which response to a fully active treatment can be compared. A number of studies using this novel approach are now in progress.In the EU, in addition to requiring data on conversion to monotherapy in refractory patients, the European Medicines Agency stipulates that a monotherapy indication in newly diagnosed epilepsy can only be granted if a candidate drug has shown at least a similar benefit/risk balance compared with an acknowledged standard at its optimal use during an assessment period of no less than 1 year. This has led to the implementation of

Transportation package design using numerical optimization

International Nuclear Information System (INIS)

Harding, D.C.; Witkowski, W.R.

1991-01-01

The purpose of this overview is twofold: first, to outline the theory and basic elements of numerical optimization; and second, to show how numerical optimization can be applied to the transportation packaging industry and used to increase efficiency and safety of radioactive and hazardous material transportation packages. A more extensive review of numerical optimization and its applications to radioactive material transportation package design was performed previously by the authors (Witkowski and Harding 1992). A proof-of-concept Type B package design is also presented as a simplified example of potential improvements achievable using numerical optimization in the design process

Transportation package design using numerical optimization

International Nuclear Information System (INIS)

Harding, D.C.; Witkowski, W.R.

1992-01-01

The design of structures and engineering systems has always been an iterative process whose complexity was dependent upon the boundary conditions, constraints and available analytical tools. Transportation packaging design is no exception with structural, thermal and radiation shielding constraints based on regulatory hypothetical accident conditions. Transportation packaging design is often accomplished by a group of specialists, each designing a single component based on one or more simple criteria, pooling results with the group, evaluating the open-quotes pooledclose quotes design, and then reiterating the entire process until a satisfactory design is reached. The manual iterative methods used by the designer/analyst can be summarized in the following steps: design the part, analyze the part, interpret the analysis results, modify the part, and re-analyze the part. The inefficiency of this design practice and the frequently conservative result suggests the need for a more structured design methodology, which can simultaneously consider all of the design constraints. Numerical optimization is a structured design methodology whose maturity in development has allowed it to become a primary design tool in many industries. The purpose of this overview is twofold: first, to outline the theory and basic elements of numerical optimization; and second, to show how numerical optimization can be applied to the transportation packaging industry and used to increase efficiency and safety of radioactive and hazardous material transportation packages. A more extensive review of numerical optimization and its applications to radioactive material transportation package design was performed previously by the authors (Witkowski and Harding 1992). A proof-of-concept Type B package design is also presented as a simplified example of potential improvements achievable using numerical optimization in the design process

Consideration of a design optimization method for advanced nuclear power plant thermal-hydraulic components

International Nuclear Information System (INIS)

Ridluan, Artit; Tokuhiro, Akira; Manic, Milos; Patterson, Michael; Danchus, William

2009-01-01

In order to meet the global energy demand and also mitigate climate change, we anticipate a significant resurgence of nuclear power in the next 50 years. Globally, Generation III plants (ABWR) have been built; Gen' III+ plants (EPR, AP1000 others) are anticipated in the near term. The U.S. DOE and Japan are respectively pursuing the NGNP and MSFR. There is renewed interest in closing the fuel cycle and gradually introducing the fast reactor into the LWR-dominated global fleet. In order to meet Generation IV criteria, i.e. thermal efficiency, inherent safety, proliferation resistance and economic competitiveness, plant and energy conversion system engineering design have to increasingly meet strict design criteria with reduced margin for reliable safety and uncertainties. Here, we considered a design optimization approach using an anticipated NGNP thermal system component as a Case Study. A systematic, efficient methodology is needed to reduce time consuming trial-and-error and computationally-intensive analyses. We thus developed a design optimization method linking three elements; that is, benchmarked CFD used as a 'design tool', artificial neural networks (ANN) to accommodate non-linear system behavior and enhancement of the 'design space', and finally, response surface methodology (RSM) to optimize the design solution with targeted constraints. The paper presents the methodology including guiding principles, an integration of CFD into design theory and practice, consideration of system non-linearities (such as fluctuating operating conditions) and systematic enhancement of the design space via application of ANN, and a stochastic optimization approach (RSM) with targeted constraints. Results from a Case Study optimizing the printed circuit heat exchanger for the NGNP energy conversion system will be presented. (author)

Interactive Reliability-Based Optimal Design

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Thoft-Christensen, Palle; Siemaszko, A.

1994-01-01

Interactive design/optimization of large, complex structural systems is considered. The objective function is assumed to model the expected costs. The constraints are reliability-based and/or related to deterministic code requirements. Solution of this optimization problem is divided in four main...... tasks, namely finite element analyses, sensitivity analyses, reliability analyses and application of an optimization algorithm. In the paper it is shown how these four tasks can be linked effectively and how existing information on design variables, Lagrange multipliers and the Hessian matrix can...

Optimization methods applied to hybrid vehicle design

Science.gov (United States)

Donoghue, J. F.; Burghart, J. H.

1983-01-01

The use of optimization methods as an effective design tool in the design of hybrid vehicle propulsion systems is demonstrated. Optimization techniques were used to select values for three design parameters (battery weight, heat engine power rating and power split between the two on-board energy sources) such that various measures of vehicle performance (acquisition cost, life cycle cost and petroleum consumption) were optimized. The apporach produced designs which were often significant improvements over hybrid designs already reported on in the literature. The principal conclusions are as follows. First, it was found that the strategy used to split the required power between the two on-board energy sources can have a significant effect on life cycle cost and petroleum consumption. Second, the optimization program should be constructed so that performance measures and design variables can be easily changed. Third, the vehicle simulation program has a significant effect on the computer run time of the overall optimization program; run time can be significantly reduced by proper design of the types of trips the vehicle takes in a one year period. Fourth, care must be taken in designing the cost and constraint expressions which are used in the optimization so that they are relatively smooth functions of the design variables. Fifth, proper handling of constraints on battery weight and heat engine rating, variables which must be large enough to meet power demands, is particularly important for the success of an optimization study. Finally, the principal conclusion is that optimization methods provide a practical tool for carrying out the design of a hybrid vehicle propulsion system.

Design of microfluidic bioreactors using topology optimization

DEFF Research Database (Denmark)

Okkels, Fridolin; Bruus, Henrik

2007-01-01

We address the design of optimal reactors for supporting biological cultures using the method of topology optimization. For some years this method have been used to design various optimal microfluidic devices.1-4 We apply this method to distribute optimally biologic cultures within a flow...

Group sequential designs for stepped-wedge cluster randomised trials.

Science.gov (United States)

Grayling, Michael J; Wason, James Ms; Mander, Adrian P

2017-10-01

The stepped-wedge cluster randomised trial design has received substantial attention in recent years. Although various extensions to the original design have been proposed, no guidance is available on the design of stepped-wedge cluster randomised trials with interim analyses. In an individually randomised trial setting, group sequential methods can provide notable efficiency gains and ethical benefits. We address this by discussing how established group sequential methodology can be adapted for stepped-wedge designs. Utilising the error spending approach to group sequential trial design, we detail the assumptions required for the determination of stepped-wedge cluster randomised trials with interim analyses. We consider early stopping for efficacy, futility, or efficacy and futility. We describe first how this can be done for any specified linear mixed model for data analysis. We then focus on one particular commonly utilised model and, using a recently completed stepped-wedge cluster randomised trial, compare the performance of several designs with interim analyses to the classical stepped-wedge design. Finally, the performance of a quantile substitution procedure for dealing with the case of unknown variance is explored. We demonstrate that the incorporation of early stopping in stepped-wedge cluster randomised trial designs could reduce the expected sample size under the null and alternative hypotheses by up to 31% and 22%, respectively, with no cost to the trial's type-I and type-II error rates. The use of restricted error maximum likelihood estimation was found to be more important than quantile substitution for controlling the type-I error rate. The addition of interim analyses into stepped-wedge cluster randomised trials could help guard against time-consuming trials conducted on poor performing treatments and also help expedite the implementation of efficacious treatments. In future, trialists should consider incorporating early stopping of some kind into

Practical considerations for adaptive trial design and implementation

CERN Document Server

Pinheiro, José; Kuznetsova, Olga

2014-01-01

This edited volume is a definitive text on adaptive clinical trial designs from creation and customization to utilization. As this book covers the full spectrum of topics involved in the adaptive designs arena, it will serve as a valuable reference for researchers working in industry, government and academia. The target audience is anyone involved in the planning and execution of clinical trials, in particular, statisticians, clinicians, pharmacometricians, clinical operation specialists, drug supply managers, and infrastructure providers.  In spite of the increased efficiency of adaptive trials in saving costs and time, ultimately getting drugs to patients sooner, their adoption in clinical development is still relatively low.  One of the chief reasons is the higher complexity of adaptive design trials as compared to traditional trials. Barriers to the use of clinical trials with adaptive features include the concerns about the integrity of study design and conduct, the risk of regulatory non-acceptance, t...

Design of Thermal Systems Using Topology Optimization

DEFF Research Database (Denmark)

Haertel, Jan Hendrik Klaas

printeddry-cooled power plant condensers using a simpliffed thermouid topology optimizationmodel is presented in another study. A benchmarking of the optimized geometriesagainst a conventional heat exchanger design is conducted and the topologyoptimized designs show a superior performance. A thermouid......The goalof this thesis is to apply topology optimization to the design of differentthermal systems such as heat sinks and heat exchangers in order to improve thethermal performance of these systems compared to conventional designs. Thedesign of thermal systems is a complex task that has...... of optimized designs are presentedwithin this thesis.  The maincontribution of the thesis is the development of several numerical optimizationmodels that are applied to different design challenges within thermalengineering.  Topology optimization isapplied in an industrial project to design the heat rejection...

Wind farm design optimization

Energy Technology Data Exchange (ETDEWEB)

Carreau, Michel; Morgenroth, Michael; Belashov, Oleg; Mdimagh, Asma; Hertz, Alain; Marcotte, Odile

2010-09-15

Innovative numerical computer tools have been developed to streamline the estimation, the design process and to optimize the Wind Farm Design with respect to the overall return on investment. The optimization engine can find the collector system layout automatically which provide a powerful tool to quickly study various alternative taking into account more precisely various constraints or factors that previously would have been too costly to analyze in details with precision. Our Wind Farm Tools have evolved through numerous projects and created value for our clients yielding Wind Farm projects with projected higher returns.

Adaptive design methods in clinical trials – a review

Directory of Open Access Journals (Sweden)

Chang Mark

2008-05-01

Full Text Available Abstract In recent years, the use of adaptive design methods in clinical research and development based on accrued data has become very popular due to its flexibility and efficiency. Based on adaptations applied, adaptive designs can be classified into three categories: prospective, concurrent (ad hoc, and retrospective adaptive designs. An adaptive design allows modifications made to trial and/or statistical procedures of ongoing clinical trials. However, it is a concern that the actual patient population after the adaptations could deviate from the originally target patient population and consequently the overall type I error (to erroneously claim efficacy for an infective drug rate may not be controlled. In addition, major adaptations of trial and/or statistical procedures of on-going trials may result in a totally different trial that is unable to address the scientific/medical questions the trial intends to answer. In this article, several commonly considered adaptive designs in clinical trials are reviewed. Impacts of ad hoc adaptations (protocol amendments, challenges in by design (prospective adaptations, and obstacles of retrospective adaptations are described. Strategies for the use of adaptive design in clinical development of rare diseases are discussed. Some examples concerning the development of Velcade intended for multiple myeloma and non-Hodgkin's lymphoma are given. Practical issues that are commonly encountered when implementing adaptive design methods in clinical trials are also discussed.

Design optimization for active twist rotor blades

Science.gov (United States)

Mok, Ji Won

This dissertation introduces the process of optimizing active twist rotor blades in the presence of embedded anisotropic piezo-composite actuators. Optimum design of active twist blades is a complex task, since it involves a rich design space with tightly coupled design variables. The study presents the development of an optimization framework for active helicopter rotor blade cross-sectional design. This optimization framework allows for exploring a rich and highly nonlinear design space in order to optimize the active twist rotor blades. Different analytical components are combined in the framework: cross-sectional analysis (UM/VABS), an automated mesh generator, a beam solver (DYMORE), a three-dimensional local strain recovery module, and a gradient based optimizer within MATLAB. Through the mathematical optimization problem, the static twist actuation performance of a blade is maximized while satisfying a series of blade constraints. These constraints are associated with locations of the center of gravity and elastic axis, blade mass per unit span, fundamental rotating blade frequencies, and the blade strength based on local three-dimensional strain fields under worst loading conditions. Through pre-processing, limitations of the proposed process have been studied. When limitations were detected, resolution strategies were proposed. These include mesh overlapping, element distortion, trailing edge tab modeling, electrode modeling and foam implementation of the mesh generator, and the initial point sensibility of the current optimization scheme. Examples demonstrate the effectiveness of this process. Optimization studies were performed on the NASA/Army/MIT ATR blade case. Even though that design was built and shown significant impact in vibration reduction, the proposed optimization process showed that the design could be improved significantly. The second example, based on a model scale of the AH-64D Apache blade, emphasized the capability of this framework to

Classical and adaptive clinical trial designs using ExpDesign Studio

National Research Council Canada - National Science Library

Chang, Mark

2008-01-01

... Relationship 2.2.9 Parallel Design 17 2.2.10 Crossover Design 17 2.2.11 Factorial Design 18 Selection of a Trial Design 18 2.3.1 Balanced Versus Unbalanced Designs 18 2.3.2 Crossover Versus Parallel...

Designing a placebo device: involving service users in clinical trial design.

Science.gov (United States)

Gooberman-Hill, Rachael; Jinks, Clare; Bouças, Sofia Barbosa; Hislop, Kelly; Dziedzic, Krysia S; Rhodes, Carol; Burston, Amanda; Adams, Jo

2013-12-01

Service users are increasingly involved in the design of clinical trials and in product and device development. Service user involvement in placebo development is crucial to a credible and acceptable placebo for clinical trials, but such involvement has not yet been reported. To enhance the design of a future clinical trial of hand splints for thumb-base osteoarthritis (OA), service users were involved in splint selection and design of a placebo splint. This article describes and reflects on this process. Two fora of service users were convened in 2011. Service users who had been prescribed a thumb splint for thumb-base OA were approached about involvement by Occupational Therapy (OT) practitioners. A total of eight service users took part in the fora. Service users discussed their experience of OA and their own splints and then tried a variety of alternative splints. Through this they identified the active features of splints alongside acceptable and unacceptable design features. Service users focused on wearability and support with or without immobilization. Fora discussed whether a placebo group ('arm') was an acceptable feature of a future trial, and service users developed a potential design for a placebo splint. This is the first project that to involve service users in placebo design. Service users are increasingly involved in product and device design and are ideally placed to identify features to make a placebo credible yet lacking key active ingredients. The future trial will include research into its acceptability. © 2013 John Wiley & Sons Ltd.

Can emergency medicine research benefit from adaptive design clinical trials?

Science.gov (United States)

Flight, Laura; Julious, Steven A; Goodacre, Steve

2017-04-01

Adaptive design clinical trials use preplanned interim analyses to determine whether studies should be stopped or modified before recruitment is complete. Emergency medicine trials are well suited to these designs as many have a short time to primary outcome relative to the length of recruitment. We hypothesised that the majority of published emergency medicine trials have the potential to use a simple adaptive trial design. We reviewed clinical trials published in three emergency medicine journals between January 2003 and December 2013. We determined the proportion that used an adaptive design as well as the proportion that could have used a simple adaptive design based on the time to primary outcome and length of recruitment. Only 19 of 188 trials included in the review were considered to have used an adaptive trial design. A total of 154/165 trials that were fixed in design had the potential to use an adaptive design. Currently, there seems to be limited uptake in the use of adaptive trial designs in emergency medicine despite their potential benefits to save time and resources. Failing to take advantage of adaptive designs could be costly to patients and research. It is recommended that where practical and logistical considerations allow, adaptive designs should be used for all emergency medicine clinical trials. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Design of acoustic devices by topology optimization

DEFF Research Database (Denmark)

Sigmund, Ole; Jensen, Jakob Søndergaard

2003-01-01

The goal of this study is to design and optimize structures and devices that are subjected to acoustic waves. Examples are acoustic lenses, sound walls, waveguides and loud speakers. We formulate the design problem as a topology optimization problem, i.e. distribute material in a design domain...... such that the acoustic response is optimized....

Comparison of optimal design methods in inverse problems

International Nuclear Information System (INIS)

Banks, H T; Holm, K; Kappel, F

2011-01-01

Typical optimal design methods for inverse or parameter estimation problems are designed to choose optimal sampling distributions through minimization of a specific cost function related to the resulting error in parameter estimates. It is hoped that the inverse problem will produce parameter estimates with increased accuracy using data collected according to the optimal sampling distribution. Here we formulate the classical optimal design problem in the context of general optimization problems over distributions of sampling times. We present a new Prohorov metric-based theoretical framework that permits one to treat succinctly and rigorously any optimal design criteria based on the Fisher information matrix. A fundamental approximation theory is also included in this framework. A new optimal design, SE-optimal design (standard error optimal design), is then introduced in the context of this framework. We compare this new design criterion with the more traditional D-optimal and E-optimal designs. The optimal sampling distributions from each design are used to compute and compare standard errors; the standard errors for parameters are computed using asymptotic theory or bootstrapping and the optimal mesh. We use three examples to illustrate ideas: the Verhulst–Pearl logistic population model (Banks H T and Tran H T 2009 Mathematical and Experimental Modeling of Physical and Biological Processes (Boca Raton, FL: Chapman and Hall/CRC)), the standard harmonic oscillator model (Banks H T and Tran H T 2009) and a popular glucose regulation model (Bergman R N, Ider Y Z, Bowden C R and Cobelli C 1979 Am. J. Physiol. 236 E667–77; De Gaetano A and Arino O 2000 J. Math. Biol. 40 136–68; Toffolo G, Bergman R N, Finegood D T, Bowden C R and Cobelli C 1980 Diabetes 29 979–90)

Comparison of optimal design methods in inverse problems

Science.gov (United States)

Banks, H. T.; Holm, K.; Kappel, F.

2011-07-01

Typical optimal design methods for inverse or parameter estimation problems are designed to choose optimal sampling distributions through minimization of a specific cost function related to the resulting error in parameter estimates. It is hoped that the inverse problem will produce parameter estimates with increased accuracy using data collected according to the optimal sampling distribution. Here we formulate the classical optimal design problem in the context of general optimization problems over distributions of sampling times. We present a new Prohorov metric-based theoretical framework that permits one to treat succinctly and rigorously any optimal design criteria based on the Fisher information matrix. A fundamental approximation theory is also included in this framework. A new optimal design, SE-optimal design (standard error optimal design), is then introduced in the context of this framework. We compare this new design criterion with the more traditional D-optimal and E-optimal designs. The optimal sampling distributions from each design are used to compute and compare standard errors; the standard errors for parameters are computed using asymptotic theory or bootstrapping and the optimal mesh. We use three examples to illustrate ideas: the Verhulst-Pearl logistic population model (Banks H T and Tran H T 2009 Mathematical and Experimental Modeling of Physical and Biological Processes (Boca Raton, FL: Chapman and Hall/CRC)), the standard harmonic oscillator model (Banks H T and Tran H T 2009) and a popular glucose regulation model (Bergman R N, Ider Y Z, Bowden C R and Cobelli C 1979 Am. J. Physiol. 236 E667-77 De Gaetano A and Arino O 2000 J. Math. Biol. 40 136-68 Toffolo G, Bergman R N, Finegood D T, Bowden C R and Cobelli C 1980 Diabetes 29 979-90).

Optimal experimental design with R

CERN Document Server

Rasch, Dieter; Verdooren, L R; Gebhardt, Albrecht

2011-01-01

Experimental design is often overlooked in the literature of applied and mathematical statistics: statistics is taught and understood as merely a collection of methods for analyzing data. Consequently, experimenters seldom think about optimal design, including prerequisites such as the necessary sample size needed for a precise answer for an experimental question. Providing a concise introduction to experimental design theory, Optimal Experimental Design with R: Introduces the philosophy of experimental design Provides an easy process for constructing experimental designs and calculating necessary sample size using R programs Teaches by example using a custom made R program package: OPDOE Consisting of detailed, data-rich examples, this book introduces experimenters to the philosophy of experimentation, experimental design, and data collection. It gives researchers and statisticians guidance in the construction of optimum experimental designs using R programs, including sample size calculations, hypothesis te...

Clinical trials in hospitalized heart failure patients: targeting interventions to optimal phenotypic subpopulations.

Science.gov (United States)

Vaduganathan, Muthiah; Butler, Javed; Roessig, Lothar; Fonarow, Gregg C; Greene, Stephen J; Metra, Marco; Cotter, Gadi; Kupfer, Stuart; Zalewski, Andrew; Sato, Naoki; Filippatos, Gerasimos; Gheorghiade, Mihai

2015-07-01

With one possible exception, the last decade of clinical trials in hospitalized heart failure (HHF) patients has failed to demonstrate improvement in long-term clinical outcomes. This trend necessitates a need to evaluate optimal drug development strategies and standards of trial conduct. It has become increasingly important to recognize the heterogeneity among HHF patients and the differential characterization of novel drug candidates. Targeting these agents to specific subpopulations may afford optimal net response related to the particular mode of action of the drug. Analyses of previous trials demonstrate profound differences in the baseline characteristics of patients enrolled across global regions and participating sites. Such differences may influence risks for events and interpretation of results. Therefore, the actual execution of trials and the epidemiology of HHF populations at the investigative sites must be taken into consideration. Collaboration among participating sites including the provision of registry data tailored to the planned development program will optimize trial conduct. Observational data prior to study initiation may enable sites to feedback and engage in protocol development to allow for feasible and valid clinical trial conduct. This site-centered, epidemiology-based network environment may facilitate studies in specific patient populations and promote optimal data collection and clear interpretation of drug safety and efficacy. This review summarizes the roundtable discussion held by a multidisciplinary team of representatives from academia, National Institutes of Health, industry, regulatory agencies, payers, and contract and academic research organizations to answer the question: Who should be targeted for novel therapies in HHF?

Optimal Design of Gravity Pipeline Systems Using Genetic Algorithm and Mathematical Optimization

Directory of Open Access Journals (Sweden)

maryam rohani

2015-03-01

Full Text Available In recent years, the optimal design of pipeline systems has become increasingly important in the water industry. In this study, the two methods of genetic algorithm and mathematical optimization were employed for the optimal design of pipeline systems with the objective of avoiding the water hammer effect caused by valve closure. The problem of optimal design of a pipeline system is a constrained one which should be converted to an unconstrained optimization problem using an external penalty function approach in the mathematical programming method. The quality of the optimal solution greatly depends on the value of the penalty factor that is calculated by the iterative method during the optimization procedure such that the computational effort is simultaneously minimized. The results obtained were used to compare the GA and mathematical optimization methods employed to determine their efficiency and capabilities for the problem under consideration. It was found that the mathematical optimization method exhibited a slightly better performance compared to the GA method.

Integrated topology and shape optimization in structural design

Science.gov (United States)

Bremicker, M.; Chirehdast, M.; Kikuchi, N.; Papalambros, P. Y.

1990-01-01

Structural optimization procedures usually start from a given design topology and vary its proportions or boundary shapes to achieve optimality under various constraints. Two different categories of structural optimization are distinguished in the literature, namely sizing and shape optimization. A major restriction in both cases is that the design topology is considered fixed and given. Questions concerning the general layout of a design (such as whether a truss or a solid structure should be used) as well as more detailed topology features (e.g., the number and connectivities of bars in a truss or the number of holes in a solid) have to be resolved by design experience before formulating the structural optimization model. Design quality of an optimized structure still depends strongly on engineering intuition. This article presents a novel approach for initiating formal structural optimization at an earlier stage, where the design topology is rigorously generated in addition to selecting shape and size dimensions. A three-phase design process is discussed: an optimal initial topology is created by a homogenization method as a gray level image, which is then transformed to a realizable design using computer vision techniques; this design is then parameterized and treated in detail by sizing and shape optimization. A fully automated process is described for trusses. Optimization of two dimensional solid structures is also discussed. Several application-oriented examples illustrate the usefulness of the proposed methodology.

Site-specific design optimization of wind turbines

DEFF Research Database (Denmark)

Fuglsang, P.; Bak, C.; Schepers, J.G.

2002-01-01

This article reports results from a European project, where site characteristics were incorporated into the design process of wind turbines, to enable site-specific design. Two wind turbines of different concept were investigated at six different sites comprising normal flat terrain, offshore...... and complex terrain wind farms. Design tools based on numerical optimization and aeroelastic calculations were combined with a cost model to allow optimization for minimum cost of energy. Different scenarios were optimized ranging from modifications of selected individual components to the complete design...... of a new wind turbine. Both annual energy yield and design-determining loads depended on site characteristics, and this represented a potential for site-specific design. The maximum variation in annual energy yield was 37% and the maximum variation in blade root fatigue loads was 62%. Optimized site...

Review of design optimization methods for turbomachinery aerodynamics

Science.gov (United States)

Li, Zhihui; Zheng, Xinqian

2017-08-01

In today's competitive environment, new turbomachinery designs need to be not only more efficient, quieter, and ;greener; but also need to be developed at on much shorter time scales and at lower costs. A number of advanced optimization strategies have been developed to achieve these requirements. This paper reviews recent progress in turbomachinery design optimization to solve real-world aerodynamic problems, especially for compressors and turbines. This review covers the following topics that are important for optimizing turbomachinery designs. (1) optimization methods, (2) stochastic optimization combined with blade parameterization methods and the design of experiment methods, (3) gradient-based optimization methods for compressors and turbines and (4) data mining techniques for Pareto Fronts. We also present our own insights regarding the current research trends and the future optimization of turbomachinery designs.

Optimal Design of Stiffeners for Bucket Foundations

DEFF Research Database (Denmark)

Courtney, William Tucker; Stolpe, Mathias; Buhl, Thomas

2015-01-01

Tosca Structure coupled with the finite element software Abaqus. The solutions to these optimization problems are then manually interpreted as a new design concept. Results show that shape optimization of the initial design can reduce stress concentrations by 38%. Additionally, topology optimization has...

Optimized design of low energy buildings

DEFF Research Database (Denmark)

Rudbeck, Claus Christian; Esbensen, Peter Kjær; Svendsen, Sv Aa Højgaard

1999-01-01

concern which can be seen during the construction of new buildings. People want energy-friendly solutions, but they should be economical optimized. An exonomical optimized building design with respect to energy consumption is the design with the lowest total cost (investment plus operational cost over its...... to evaluate different separate solutions when they interact in the building.When trying to optimize several parameters there is a need for a method, which will show the correct price-performance of each part of a building under design. The problem with not having such a method will first be showed...

On simultaneous shape and orientational design for eigenfrequency optimization

DEFF Research Database (Denmark)

Pedersen, Niels Leergaard

2007-01-01

Plates with an internal hole of fixed area are designed in order to maximize the performance with respect to eigenfrequencies. The optimization is performed by simultaneous shape, material, and orientational design. The shape of the hole is designed, and the material design is the design of an or......Plates with an internal hole of fixed area are designed in order to maximize the performance with respect to eigenfrequencies. The optimization is performed by simultaneous shape, material, and orientational design. The shape of the hole is designed, and the material design is the design...... of an orthotropic material that can be considered as a fiber-net within each finite element. This fiber-net is optimally oriented in the individual elements of the finite element discretization. The optimizations are performed using the finite element method for analysis, and the optimization approach is a two......-step method. In the first step, we find the best design on the basis of a recursive optimization procedure based on optimality criteria. In the second step, mathematical programming and sensitivity analysis are applied to find the final optimized design....

Application of Reduced Order Transonic Aerodynamic Influence Coefficient Matrix for Design Optimization

Science.gov (United States)

Pak, Chan-gi; Li, Wesley W.

2009-01-01

Supporting the Aeronautics Research Mission Directorate guidelines, the National Aeronautics and Space Administration [NASA] Dryden Flight Research Center is developing a multidisciplinary design, analysis, and optimization [MDAO] tool. This tool will leverage existing tools and practices, and allow the easy integration and adoption of new state-of-the-art software. Today s modern aircraft designs in transonic speed are a challenging task due to the computation time required for the unsteady aeroelastic analysis using a Computational Fluid Dynamics [CFD] code. Design approaches in this speed regime are mainly based on the manual trial and error. Because of the time required for unsteady CFD computations in time-domain, this will considerably slow down the whole design process. These analyses are usually performed repeatedly to optimize the final design. As a result, there is considerable motivation to be able to perform aeroelastic calculations more quickly and inexpensively. This paper will describe the development of unsteady transonic aeroelastic design methodology for design optimization using reduced modeling method and unsteady aerodynamic approximation. The method requires the unsteady transonic aerodynamics be represented in the frequency or Laplace domain. Dynamically linear assumption is used for creating Aerodynamic Influence Coefficient [AIC] matrices in transonic speed regime. Unsteady CFD computations are needed for the important columns of an AIC matrix which corresponded to the primary modes for the flutter. Order reduction techniques, such as Guyan reduction and improved reduction system, are used to reduce the size of problem transonic flutter can be found by the classic methods, such as Rational function approximation, p-k, p, root-locus etc. Such a methodology could be incorporated into MDAO tool for design optimization at a reasonable computational cost. The proposed technique is verified using the Aerostructures Test Wing 2 actually designed

Design of a multi-arm randomized clinical trial with no control arm.

Science.gov (United States)

Magaret, Amalia; Angus, Derek C; Adhikari, Neill K J; Banura, Patrick; Kissoon, Niranjan; Lawler, James V; Jacob, Shevin T

2016-01-01

Clinical trial designs that include multiple treatments are currently limited to those that perform pairwise comparisons of each investigational treatment to a single control. However, there are settings, such as the recent Ebola outbreak, in which no treatment has been demonstrated to be effective; and therefore, no standard of care exists which would serve as an appropriate control. For illustrative purposes, we focused on the care of patients presenting in austere settings with critically ill 'sepsis-like' syndromes. Our approach involves a novel algorithm for comparing mortality among arms without requiring a single fixed control. The algorithm allows poorly-performing arms to be dropped during interim analyses. Consequently, the study may be completed earlier than planned. We used simulation to determine operating characteristics for the trial and to estimate the required sample size. We present a potential study design targeting a minimal effect size of a 23% relative reduction in mortality between any pair of arms. Using estimated power and spurious significance rates from the simulated scenarios, we show that such a trial would require 2550 participants. Over a range of scenarios, our study has 80 to 99% power to select the optimal treatment. Using a fixed control design, if the control arm is least efficacious, 640 subjects would be enrolled into the least efficacious arm, while our algorithm would enroll between 170 and 430. This simulation method can be easily extended to other settings or other binary outcomes. Early dropping of arms is efficient and ethical when conducting clinical trials with multiple arms. Copyright © 2015 Elsevier Inc. All rights reserved.

Reliability-Based Robust Design Optimization of Structures Considering Uncertainty in Design Variables

Directory of Open Access Journals (Sweden)

Shujuan Wang

2015-01-01

Full Text Available This paper investigates the structural design optimization to cover both the reliability and robustness under uncertainty in design variables. The main objective is to improve the efficiency of the optimization process. To address this problem, a hybrid reliability-based robust design optimization (RRDO method is proposed. Prior to the design optimization, the Sobol sensitivity analysis is used for selecting key design variables and providing response variance as well, resulting in significantly reduced computational complexity. The single-loop algorithm is employed to guarantee the structural reliability, allowing fast optimization process. In the case of robust design, the weighting factor balances the response performance and variance with respect to the uncertainty in design variables. The main contribution of this paper is that the proposed method applies the RRDO strategy with the usage of global approximation and the Sobol sensitivity analysis, leading to the reduced computational cost. A structural example is given to illustrate the performance of the proposed method.

Design and Optimization of a Turbine Intake Structure

Directory of Open Access Journals (Sweden)

P. Fošumpaur

2005-01-01

Full Text Available The appropriate design of the turbine intake structure of a hydropower plant is based on assumptions about its suitable function, and the design will increase the total efficiency of operation. This paper deals with optimal design of the turbine structure of run-of-river hydropower plants. The study focuses mainly on optimization of the hydropower plant location with respect to the original river banks, and on the optimal design of a separating pier between the weir and the power plant. The optimal design of the turbine intake was determined with the use of 2-D mathematical modelling. A case study is performed for the optimal design of a turbine intake structure on the Nemen river in Belarus. 

LMI–based robust controller design approach in aircraft multidisciplinary design optimization problem

Directory of Open Access Journals (Sweden)

Qinghua Zeng

2015-07-01

Full Text Available This article proposes a linear matrix inequality–based robust controller design approach to implement the synchronous design of aircraft control discipline and other disciplines, in which the variation in design parameters is treated as equivalent perturbations. Considering the complicated mapping relationships between the coefficient arrays of aircraft motion model and the aircraft design parameters, the robust controller designed is directly based on the variation in these coefficient arrays so conservative that the multidisciplinary design optimization problem would be too difficult to solve, or even if there is a solution, the robustness of design result is generally poor. Therefore, this article derives the uncertainty model of disciplinary design parameters based on response surface approximation, converts the design problem of the robust controller into a problem of solving a standard linear matrix inequality, and theoretically gives a less conservative design method of the robust controller which is based on the variation in design parameters. Furthermore, the concurrent subspace approach is applied to the multidisciplinary system with this kind of robust controller in the design loop. A multidisciplinary design optimization of a tailless aircraft as example is shown that control discipline can be synchronous optimal design with other discipline, especially this method will greatly reduce the calculated amount of multidisciplinary design optimization and make multidisciplinary design optimization results more robustness of flight performance.

Problem statement for optimal design of steel structures

Directory of Open Access Journals (Sweden)

Ginzburg Aleksandr Vital'evich

2014-07-01

Full Text Available The presented article considers the following complex of tasks. The main stages of the life cycle of a building construction with the indication of process entrance and process exit are described. Requirements imposed on steel constructions are considered. The optimum range of application for steel designs is specified, as well as merits and demerits of a design material. The nomenclature of metal designs is listed - the block diagram is constructed. Possible optimality criteria of steel designs, offered by various authors for various types of constructions are considered. It is established that most often the criterion of a minimum of design mass is accepted as criterion of optimality; more rarely - a minimum of the given expenses, a minimum of a design cost in business. In the present article special attention is paid to a type of objective function of optimization problem. It is also established that depending on the accepted optimality criterion, the use of different types of functions is possible. This complexity of objective function depends on completeness of optimality criterion application. In the work the authors consider the following objective functions: the mass of the main element of a design; objective function by criterion of factory cost; objective function by criterion of cost in business. According to these examples it can be seen that objective functions by the criteria of labor expenses for production of designs are generally non-linear, which complicates solving the optimization problem. Another important factor influencing the problem of optimal design solution for steel designs, which is analyzed, is account for operating restrictions. In the article 8 groups of restrictions are analyzed. Attempts to completely account for the parameters of objective function optimized by particular optimality criteria, taking into account all the operating restrictions, considerably complicates the problem of designing. For solving this

Optimization design of blade shapes for wind turbines

DEFF Research Database (Denmark)

Chen, Jin; Wang, Xudong; Shen, Wen Zhong

2010-01-01

For the optimization design of wind turbines, the new normal and tangential induced factors of wind turbines are given considering the tip loss of the normal and tangential forces based on the blade element momentum theory and traditional aerodynamic model. The cost model of the wind turbines...... and the optimization design model are developed. In the optimization model, the objective is the minimum cost of energy and the design variables are the chord length, twist angle and the relative thickness. Finally, the optimization is carried out for a 2 MW blade by using this optimization design model....... The performance of blades is validated through the comparison and analysis of the results. The reduced cost shows that the optimization model is good enough for the design of wind turbines. The results give a proof for the design and research on the blades of large scale wind turbines and also establish...

A Review of Design Optimization Methods for Electrical Machines

Directory of Open Access Journals (Sweden)

Gang Lei

2017-11-01

Full Text Available Electrical machines are the hearts of many appliances, industrial equipment and systems. In the context of global sustainability, they must fulfill various requirements, not only physically and technologically but also environmentally. Therefore, their design optimization process becomes more and more complex as more engineering disciplines/domains and constraints are involved, such as electromagnetics, structural mechanics and heat transfer. This paper aims to present a review of the design optimization methods for electrical machines, including design analysis methods and models, optimization models, algorithms and methods/strategies. Several efficient optimization methods/strategies are highlighted with comments, including surrogate-model based and multi-level optimization methods. In addition, two promising and challenging topics in both academic and industrial communities are discussed, and two novel optimization methods are introduced for advanced design optimization of electrical machines. First, a system-level design optimization method is introduced for the development of advanced electric drive systems. Second, a robust design optimization method based on the design for six-sigma technique is introduced for high-quality manufacturing of electrical machines in production. Meanwhile, a proposal is presented for the development of a robust design optimization service based on industrial big data and cloud computing services. Finally, five future directions are proposed, including smart design optimization method for future intelligent design and production of electrical machines.

Evaluating the optimal timing of surgical antimicrobial prophylaxis: study protocol for a randomized controlled trial.

Science.gov (United States)

Mujagic, Edin; Zwimpfer, Tibor; Marti, Walter R; Zwahlen, Marcel; Hoffmann, Henry; Kindler, Christoph; Fux, Christoph; Misteli, Heidi; Iselin, Lukas; Lugli, Andrea Kopp; Nebiker, Christian A; von Holzen, Urs; Vinzens, Fabrizio; von Strauss, Marco; Reck, Stefan; Kraljević, Marko; Widmer, Andreas F; Oertli, Daniel; Rosenthal, Rachel; Weber, Walter P

2014-05-24

Surgical site infections are the most common hospital-acquired infections among surgical patients. The administration of surgical antimicrobial prophylaxis reduces the risk of surgical site infections . The optimal timing of this procedure is still a matter of debate. While most studies suggest that it should be given as close to the incision time as possible, others conclude that this may be too late for optimal prevention of surgical site infections. A large observational study suggests that surgical antimicrobial prophylaxis should be administered 74 to 30 minutes before surgery. The aim of this article is to report the design and protocol of a randomized controlled trial investigating the optimal timing of surgical antimicrobial prophylaxis. In this bi-center randomized controlled trial conducted at two tertiary referral centers in Switzerland, we plan to include 5,000 patients undergoing general, oncologic, vascular and orthopedic trauma procedures. Patients are randomized in a 1:1 ratio into two groups: one receiving surgical antimicrobial prophylaxis in the anesthesia room (75 to 30 minutes before incision) and the other receiving surgical antimicrobial prophylaxis in the operating room (less than 30 minutes before incision). We expect a significantly lower rate of surgical site infections with surgical antimicrobial prophylaxis administered more than 30 minutes before the scheduled incision. The primary outcome is the occurrence of surgical site infections during a 30-day follow-up period (one year with an implant in place). When assuming a 5% surgical site infection risk with administration of surgical antimicrobial prophylaxis in the operating room, the planned sample size has an 80% power to detect a relative risk reduction for surgical site infections of 33% when administering surgical antimicrobial prophylaxis in the anesthesia room (with a two-sided type I error of 5%). We expect the study to be completed within three years. The results of this

Enhancing product robustness in reliability-based design optimization

International Nuclear Information System (INIS)

Zhuang, Xiaotian; Pan, Rong; Du, Xiaoping

2015-01-01

Different types of uncertainties need to be addressed in a product design optimization process. In this paper, the uncertainties in both product design variables and environmental noise variables are considered. The reliability-based design optimization (RBDO) is integrated with robust product design (RPD) to concurrently reduce the production cost and the long-term operation cost, including quality loss, in the process of product design. This problem leads to a multi-objective optimization with probabilistic constraints. In addition, the model uncertainties associated with a surrogate model that is derived from numerical computation methods, such as finite element analysis, is addressed. A hierarchical experimental design approach, augmented by a sequential sampling strategy, is proposed to construct the response surface of product performance function for finding optimal design solutions. The proposed method is demonstrated through an engineering example. - Highlights: • A unifying framework for integrating RBDO and RPD is proposed. • Implicit product performance function is considered. • The design problem is solved by sequential optimization and reliability assessment. • A sequential sampling technique is developed for improving design optimization. • The comparison with traditional RBDO is provided

Applying Probabilistic Decision Models to Clinical Trial Design

Science.gov (United States)

Smith, Wade P; Phillips, Mark H

2018-01-01

Clinical trial design most often focuses on a single or several related outcomes with corresponding calculations of statistical power. We consider a clinical trial to be a decision problem, often with competing outcomes. Using a current controversy in the treatment of HPV-positive head and neck cancer, we apply several different probabilistic methods to help define the range of outcomes given different possible trial designs. Our model incorporates the uncertainties in the disease process and treatment response and the inhomogeneities in the patient population. Instead of expected utility, we have used a Markov model to calculate quality adjusted life expectancy as a maximization objective. Monte Carlo simulations over realistic ranges of parameters are used to explore different trial scenarios given the possible ranges of parameters. This modeling approach can be used to better inform the initial trial design so that it will more likely achieve clinical relevance.

Optimal Design of Pumped Pipeline Systems Using Genetic Algorithm and Mathematical Optimization

Directory of Open Access Journals (Sweden)

Mohammadhadi Afshar

2007-12-01

Full Text Available In recent years, much attention has been paid to the optimal design of pipeline systems. In this study, the problem of pipeline system optimal design has been solved through genetic algorithm and mathematical optimization. Pipe diameters and their thicknesses are considered as decision variables to be designed in a manner that water column separation and excessive pressures are avoided in the event of pump failure. Capabilities of the genetic algorithm and the mathematical programming method are compared for the problem under consideration. For simulation of transient streams, explicit characteristic method is used in which devices such as pumps are defined as boundary conditions of the equations defining the hydraulic behavior of pipe segments. The problem of optimal design of pipeline systems is a constrained problem which is converted to an unconstrained optimization problem using an external penalty function approach. The efficiency of the proposed approaches is verified in one example and the results are presented.

Interpreting clinical trial results by deductive reasoning: In search of improved trial design.

Science.gov (United States)

Kurbel, Sven; Mihaljević, Slobodan

2017-10-01

Clinical trial results are often interpreted by inductive reasoning, in a trial design-limited manner, directed toward modifications of the current clinical practice. Deductive reasoning is an alternative in which results of relevant trials are combined in indisputable premises that lead to a conclusion easily testable in future trials. © 2017 WILEY Periodicals, Inc.

Design and fabrication of topologically optimized structures;

DEFF Research Database (Denmark)

Feringa, Jelle; Søndergaard, Asbjørn

2012-01-01

Integral structural optimization and fabrication seeks the synthesis of two original approaches; that of topological optimization (TO) and robotic hotwire cutting (HWC) (Mcgee 2011). TO allows for the reduction of up to 70% of the volume of concrete to support a given structure (Sondergaard...... & Dombernowsky 2011). A strength of the method is that it allows to come up with structural designs that lie beyond the grasp of traditional means of design. A design space is a discretized volume, delimiting where the optimization will take place. The number of cells used to discretize the design space thus...

Pragmatic trial design elements showed a different impact on trial interpretation and feasibility than explanatory elements

NARCIS (Netherlands)

Nieuwenhuis, Joost B.; Irving, Elaine; Oude Rengerink, Katrien; Lloyd, Emily; Goetz, Iris; Grobbee, Diederick E.; Stolk, Pieter; Groenwold, Rolf H H; Zuidgeest, Mira G P

2016-01-01

OBJECTIVE: To illustrate how pragmatic trial design elements, or inserting explanatory trial elements in pragmatic trials affect validity, generalizability, precision and operational feasibility. STUDY DESIGN AND SETTING: From illustrative examples identified through the IMI Get Real Consortium, we

A surrogate based multistage-multilevel optimization procedure for multidisciplinary design optimization

NARCIS (Netherlands)

Yao, W.; Chen, X.; Ouyang, Q.; Van Tooren, M.

2011-01-01

Optimization procedure is one of the key techniques to address the computational and organizational complexities of multidisciplinary design optimization (MDO). Motivated by the idea of synthetically exploiting the advantage of multiple existing optimization procedures and meanwhile complying with

Design of the BRISC study: a multicentre controlled clinical trial to optimize the communication of breast cancer risks in genetic counselling.

Science.gov (United States)

Ockhuysen-Vermey, Caroline F; Henneman, Lidewij; van Asperen, Christi J; Oosterwijk, Jan C; Menko, Fred H; Timmermans, Daniëlle R M

2008-10-03

Understanding risks is considered to be crucial for informed decision-making. Inaccurate risk perception is a common finding in women with a family history of breast cancer attending genetic counseling. As yet, it is unclear how risks should best be communicated in clinical practice. This study protocol describes the design and methods of the BRISC (Breast cancer RISk Communication) study evaluating the effect of different formats of risk communication on the counsellee's risk perception, psychological well-being and decision-making regarding preventive options for breast cancer. The BRISC study is designed as a pre-post-test controlled group intervention trial with repeated measurements using questionnaires. The intervention-an additional risk consultation-consists of one of 5 conditions that differ in the way counsellee's breast cancer risk is communicated: 1) lifetime risk in numerical format (natural frequencies, i.e. X out of 100), 2) lifetime risk in both numerical format and graphical format (population figures), 3) lifetime risk and age-related risk in numerical format, 4) lifetime risk and age-related risk in both numerical format and graphical format, and 5) lifetime risk in percentages. Condition 6 is the control condition in which no intervention is given (usual care). Participants are unaffected women with a family history of breast cancer attending one of three participating clinical genetic centres in the Netherlands. The BRISC study allows for an evaluation of the effects of different formats of communicating breast cancer risks to counsellees. The results can be used to optimize risk communication in order to improve informed decision-making among women with a family history of breast cancer. They may also be useful for risk communication in other health-related services. Current Controlled Trials ISRCTN14566836.

Telemanipulator design and optimization software

Science.gov (United States)

Cote, Jean; Pelletier, Michel

1995-12-01

For many years, industrial robots have been used to execute specific repetitive tasks. In those cases, the optimal configuration and location of the manipulator only has to be found once. The optimal configuration or position where often found empirically according to the tasks to be performed. In telemanipulation, the nature of the tasks to be executed is much wider and can be very demanding in terms of dexterity and workspace. The position/orientation of the robot's base could be required to move during the execution of a task. At present, the choice of the initial position of the teleoperator is usually found empirically which can be sufficient in the case of an easy or repetitive task. In the converse situation, the amount of time wasted to move the teleoperator support platform has to be taken into account during the execution of the task. Automatic optimization of the position/orientation of the platform or a better designed robot configuration could minimize these movements and save time. This paper will present two algorithms. The first algorithm is used to optimize the position and orientation of a given manipulator (or manipulators) with respect to the environment on which a task has to be executed. The second algorithm is used to optimize the position or the kinematic configuration of a robot. For this purpose, the tasks to be executed are digitized using a position/orientation measurement system and a compact representation based on special octrees. Given a digitized task, the optimal position or Denavit-Hartenberg configuration of the manipulator can be obtained numerically. Constraints on the robot design can also be taken into account. A graphical interface has been designed to facilitate the use of the two optimization algorithms.

Optimal Design of Porous Materials

DEFF Research Database (Denmark)

Andreassen, Erik

The focus of this thesis is topology optimization of material microstructures. That is, creating new materials, with attractive properties, by combining classic materials in periodic patterns. First, large-scale topology optimization is used to design complicated three-dimensional materials......, throughout the thesis extra attention is given to obtain structures that can be manufactured. That is also the case in the final part, where a simple multiscale method for the optimization of structural damping is presented. The method can be used to obtain an optimized component with structural details...

I-optimal mixture designs

OpenAIRE

GOOS, Peter; JONES, Bradley; SYAFITRI, Utami

2013-01-01

In mixture experiments, the factors under study are proportions of the ingredients of a mixture. The special nature of the factors in a mixture experiment necessitates specific types of regression models, and specific types of experimental designs. Although mixture experiments usually are intended to predict the response(s) for all possible formulations of the mixture and to identify optimal proportions for each of the ingredients, little research has been done concerning their I-optimal desi...

Optimal design of lossy bandgap structures

DEFF Research Database (Denmark)

Jensen, Jakob Søndergaard

2004-01-01

The method of topology optimization is used to design structures for wave propagation with one lossy material component. Optimized designs for scalar elastic waves are presented for mininimum wave transmission as well as for maximum wave energy dissipation. The structures that are obtained...... are of the 1D or 2D bandgap type depending on the objective and the material parameters....

The Managed Ventricular pacing versus VVI 40 Pacing (MVP) Trial: clinical background, rationale, design, and implementation.

Science.gov (United States)

Sweeney, Michael O; Ellenbogen, Kenneth A; Miller, Elaine Hogan; Sherfesee, Lou; Sheldon, Todd; Whellan, David

2006-12-01

Implantable cardioverter defibrillators (ICDs) reduce mortality among appropriately selected patients who have had or are at risk for life-threatening ventricular arrhythmia. Right ventricular apical (RVA) pacing has been implicated in worsening heart failure and death. The optimal pacemaker mode for bradycardia support while minimizing unnecessary and potentially harmful RVA pacing has not been determined. The Managed Ventricular pacing vs. VVI 40 Pacing Trial (MVP) is a prospective, multicenter, randomized, single-blind, parallel, controlled clinical trial designed to establish whether atrial-based dual-chamber managed ventricular pacing mode (MVP) is equivalent or superior to back-up only ventricular pacing (VVI 40) among patients with standard indications for ICD therapy and no indication for bradycardia pacing. The MVP Trial is designed with 80% power to detect a 10% reduction in the primary endpoint of new or worsening heart failure or all-cause mortality in the MVP-treated group. Approximately 1,000 patients at 80 centers in the United States, Canada, Western Europe, and Israel will be randomized to MVP or VVI 40 pacing after successful implantation of a dual-chamber ICD. Heart failure therapies will be optimized in accordance with evidence-based guidelines. Prespecified secondary endpoints will include ventricular arrhythmias, atrial fibrillation, new indication for bradycardia pacing, health-related quality of life, and cost effectiveness. Enrollment began in October 2004 and concluded in April 2006. The study will be terminated upon recommendation of the Data Monitoring Committee or when the last patient enrolled and surviving has reached a minimum 2 years of follow-up. The MVP Trial will meet the clinical need for carefully designed prospective studies to define the benefits of atrial-based dual-chamber minimal ventricular pacing versus single-chamber ventricular pacing in conventional ICD patients.

Design, analysis and presentation of factorial randomised controlled trials

Directory of Open Access Journals (Sweden)

Little Paul

2003-11-01

Full Text Available Abstract Background The evaluation of more than one intervention in the same randomised controlled trial can be achieved using a parallel group design. However this requires increased sample size and can be inefficient, especially if there is also interest in considering combinations of the interventions. An alternative may be a factorial trial, where for two interventions participants are allocated to receive neither intervention, one or the other, or both. Factorial trials require special considerations, however, particularly at the design and analysis stages. Discussion Using a 2 × 2 factorial trial as an example, we present a number of issues that should be considered when planning a factorial trial. The main design issue is that of sample size. Factorial trials are most often powered to detect the main effects of interventions, since adequate power to detect plausible interactions requires greatly increased sample sizes. The main analytical issues relate to the investigation of main effects and the interaction between the interventions in appropriate regression models. Presentation of results should reflect the analytical strategy with an emphasis on the principal research questions. We also give an example of how baseline and follow-up data should be presented. Lastly, we discuss the implications of the design, analytical and presentational issues covered. Summary Difficulties in interpreting the results of factorial trials if an influential interaction is observed is the cost of the potential for efficient, simultaneous consideration of two or more interventions. Factorial trials can in principle be designed to have adequate power to detect realistic interactions, and in any case they are the only design that allows such effects to be investigated.

Collaborative Systems Driven Aircraft Configuration Design Optimization

OpenAIRE

Shiva Prakasha, Prajwal; Ciampa, Pier Davide; Nagel, Björn

2016-01-01

A Collaborative, Inside-Out Aircraft Design approach is presented in this paper. An approach using physics based analysis to evaluate the correlations between the airframe design, as well as sub-systems integration from the early design process, and to exploit the synergies within a simultaneous optimization process. Further, the disciplinary analysis modules involved in the optimization task are located in different organization. Hence, the Airframe and Subsystem design tools are integrated ...

Parametric Optimization of Hospital Design

DEFF Research Database (Denmark)

Holst, Malene Kirstine; Kirkegaard, Poul Henning; Christoffersen, L.D.

2013-01-01

Present paper presents a parametric performancebased design model for optimizing hospital design. The design model operates with geometric input parameters defining the functional requirements of the hospital and input parameters in terms of performance objectives defining the design requirements...... and preferences of the hospital with respect to performances. The design model takes point of departure in the hospital functionalities as a set of defined parameters and rules describing the design requirements and preferences....

Solid Rocket Motor Design Using Hybrid Optimization

Directory of Open Access Journals (Sweden)

Kevin Albarado

2012-01-01

Full Text Available A particle swarm/pattern search hybrid optimizer was used to drive a solid rocket motor modeling code to an optimal solution. The solid motor code models tapered motor geometries using analytical burn back methods by slicing the grain into thin sections along the axial direction. Grains with circular perforated stars, wagon wheels, and dog bones can be considered and multiple tapered sections can be constructed. The hybrid approach to optimization is capable of exploring large areas of the solution space through particle swarming, but is also able to climb “hills” of optimality through gradient based pattern searching. A preliminary method for designing tapered internal geometry as well as tapered outer mold-line geometry is presented. A total of four optimization cases were performed. The first two case studies examines designing motors to match a given regressive-progressive-regressive burn profile. The third case study studies designing a neutrally burning right circular perforated grain (utilizing inner and external geometry tapering. The final case study studies designing a linearly regressive burning profile for right circular perforated (tapered grains.

Design optimization of axial flow hydraulic turbine runner: Part II - multi-objective constrained optimization method

Science.gov (United States)

Peng, Guoyi; Cao, Shuliang; Ishizuka, Masaru; Hayama, Shinji

2002-06-01

This paper is concerned with the design optimization of axial flow hydraulic turbine runner blade geometry. In order to obtain a better design plan with good performance, a new comprehensive performance optimization procedure has been presented by combining a multi-variable multi-objective constrained optimization model with a Q3D inverse computation and a performance prediction procedure. With careful analysis of the inverse design of axial hydraulic turbine runner, the total hydraulic loss and the cavitation coefficient are taken as optimization objectives and a comprehensive objective function is defined using the weight factors. Parameters of a newly proposed blade bound circulation distribution function and parameters describing positions of blade leading and training edges in the meridional flow passage are taken as optimization variables.The optimization procedure has been applied to the design optimization of a Kaplan runner with specific speed of 440 kW. Numerical results show that the performance of designed runner is successfully improved through optimization computation. The optimization model is found to be validated and it has the feature of good convergence. With the multi-objective optimization model, it is possible to control the performance of designed runner by adjusting the value of weight factors defining the comprehensive objective function. Copyright

Application of surrogate-based global optimization to aerodynamic design

CERN Document Server

Pérez, Esther

2016-01-01

Aerodynamic design, like many other engineering applications, is increasingly relying on computational power. The growing need for multi-disciplinarity and high fidelity in design optimization for industrial applications requires a huge number of repeated simulations in order to find an optimal design candidate. The main drawback is that each simulation can be computationally expensive – this becomes an even bigger issue when used within parametric studies, automated search or optimization loops, which typically may require thousands of analysis evaluations. The core issue of a design-optimization problem is the search process involved. However, when facing complex problems, the high-dimensionality of the design space and the high-multi-modality of the target functions cannot be tackled with standard techniques. In recent years, global optimization using meta-models has been widely applied to design exploration in order to rapidly investigate the design space and find sub-optimal solutions. Indeed, surrogat...

Optimal design of the heat pipe using TLBO (teaching–learning-based optimization) algorithm

International Nuclear Information System (INIS)

Rao, R.V.; More, K.C.

2015-01-01

Heat pipe is a highly efficient and reliable heat transfer component. It is a closed container designed to transfer a large amount of heat in system. Since the heat pipe operates on a closed two-phase cycle, the heat transfer capacity is greater than for solid conductors. Also, the thermal response time is less than with solid conductors. The three major elemental parts of the rotating heat pipe are: a cylindrical evaporator, a truncated cone condenser, and a fixed amount of working fluid. In this paper, a recently proposed new stochastic advanced optimization algorithm called TLBO (Teaching–Learning-Based Optimization) algorithm is used for single objective as well as multi-objective design optimization of heat pipe. It is easy to implement, does not make use of derivatives and it can be applied to unconstrained or constrained problems. Two examples of heat pipe are presented in this paper. The results of application of TLBO algorithm for the design optimization of heat pipe are compared with the NPGA (Niched Pareto Genetic Algorithm), GEM (Grenade Explosion Method) and GEO (Generalized External optimization). It is found that the TLBO algorithm has produced better results as compared to those obtained by using NPGA, GEM and GEO algorithms. - Highlights: • The TLBO (Teaching–Learning-Based Optimization) algorithm is used for the design and optimization of a heat pipe. • Two examples of heat pipe design and optimization are presented. • The TLBO algorithm is proved better than the other optimization algorithms in terms of results and the convergence

Blood pressure and LDL-cholesterol targets for prevention of recurrent strokes and cognitive decline in the hypertensive patient: design of the European Society of Hypertension-Chinese Hypertension League Stroke in Hypertension Optimal Treatment randomized trial.

Science.gov (United States)

Zanchetti, Alberto; Liu, Lisheng; Mancia, Giuseppe; Parati, Gianfranco; Grassi, Guido; Stramba-Badiale, Marco; Silani, Vincenzo; Bilo, Grzegorz; Corrao, Giovanni; Zambon, Antonella; Scotti, Lorenza; Zhang, Xinhua; Wang, HayYan; Zhang, Yuqing; Zhang, Xuezhong; Guan, Ting Rui; Berge, Eivind; Redon, Josep; Narkiewicz, Krzysztof; Dominiczak, Anna; Nilsson, Peter; Viigimaa, Margus; Laurent, Stéphane; Agabiti-Rosei, Enrico; Wu, Zhaosu; Zhu, Dingliang; Rodicio, José Luis; Ruilope, Luis Miguel; Martell-Claros, Nieves; Pinto, Fernando; Schmieder, Roland E; Burnier, Michel; Banach, Maciej; Cifkova, Renata; Farsang, Csaba; Konradi, Alexandra; Lazareva, Irina; Sirenko, Yuriy; Dorobantu, Maria; Postadzhiyan, Arman; Accetto, Rok; Jelakovic, Bojan; Lovic, Dragan; Manolis, Athanasios J; Stylianou, Philippos; Erdine, Serap; Dicker, Dror; Wei, Gangzhi; Xu, Chengbin; Xie, Hengge; Coca, Antonio; O'Brien, John; Ford, Gary

2014-09-01

The SBP values to be achieved by antihypertensive therapy in order to maximize reduction of cardiovascular outcomes are unknown; neither is it clear whether in patients with a previous cardiovascular event, the optimal values are lower than in the low-to-moderate risk hypertensive patients, or a more cautious blood pressure (BP) reduction should be obtained. Because of the uncertainty whether 'the lower the better' or the 'J-curve' hypothesis is correct, the European Society of Hypertension and the Chinese Hypertension League have promoted a randomized trial comparing antihypertensive treatment strategies aiming at three different SBP targets in hypertensive patients with a recent stroke or transient ischaemic attack. As the optimal level of low-density lipoprotein cholesterol (LDL-C) level is also unknown in these patients, LDL-C-lowering has been included in the design. The European Society of Hypertension-Chinese Hypertension League Stroke in Hypertension Optimal Treatment trial is a prospective multinational, randomized trial with a 3 × 2 factorial design comparing: three different SBP targets (1, hypertension and a stroke or transient ischaemic attack 1-6 months before randomization. Antihypertensive and statin treatments will be initiated or modified using suitable registered agents chosen by the investigators, in order to maintain patients within the randomized SBP and LDL-C windows. All patients will be followed up every 3 months for BP and every 6 months for LDL-C. Ambulatory BP will be measured yearly. Primary outcome is time to stroke (fatal and non-fatal). Important secondary outcomes are: time to first major cardiovascular event; cognitive decline (Montreal Cognitive Assessment) and dementia. All major outcomes will be adjudicated by committees blind to randomized allocation. A Data and Safety Monitoring Board has open access to data and can recommend trial interruption for safety. It has been calculated that 925 patients would reach the primary

A Bayesian approach for incorporating economic factors in sample size design for clinical trials of individual drugs and portfolios of drugs.

Science.gov (United States)

Patel, Nitin R; Ankolekar, Suresh

2007-11-30

Classical approaches to clinical trial design ignore economic factors that determine economic viability of a new drug. We address the choice of sample size in Phase III trials as a decision theory problem using a hybrid approach that takes a Bayesian view from the perspective of a drug company and a classical Neyman-Pearson view from the perspective of regulatory authorities. We incorporate relevant economic factors in the analysis to determine the optimal sample size to maximize the expected profit for the company. We extend the analysis to account for risk by using a 'satisficing' objective function that maximizes the chance of meeting a management-specified target level of profit. We extend the models for single drugs to a portfolio of clinical trials and optimize the sample sizes to maximize the expected profit subject to budget constraints. Further, we address the portfolio risk and optimize the sample sizes to maximize the probability of achieving a given target of expected profit.

Optimal dose selection accounting for patient subpopulations in a randomized Phase II trial to maximize the success probability of a subsequent Phase III trial.

Science.gov (United States)

Takahashi, Fumihiro; Morita, Satoshi

2018-02-08

Phase II clinical trials are conducted to determine the optimal dose of the study drug for use in Phase III clinical trials while also balancing efficacy and safety. In conducting these trials, it may be important to consider subpopulations of patients grouped by background factors such as drug metabolism and kidney and liver function. Determining the optimal dose, as well as maximizing the effectiveness of the study drug by analyzing patient subpopulations, requires a complex decision-making process. In extreme cases, drug development has to be terminated due to inadequate efficacy or severe toxicity. Such a decision may be based on a particular subpopulation. We propose a Bayesian utility approach (BUART) to randomized Phase II clinical trials which uses a first-order bivariate normal dynamic linear model for efficacy and safety in order to determine the optimal dose and study population in a subsequent Phase III clinical trial. We carried out a simulation study under a wide range of clinical scenarios to evaluate the performance of the proposed method in comparison with a conventional method separately analyzing efficacy and safety in each patient population. The proposed method showed more favorable operating characteristics in determining the optimal population and dose.

Selection of a design for response surface

Science.gov (United States)

Ranade, Shruti Sunil; Thiagarajan, Padma

2017-11-01

Box-Behnken, Central-Composite, D and I-optimal designs were compared using statistical tools. Experimental trials for all designs were generated. Random uniform responses were simulated for all models. R-square, Akaike and Bayesian Information Criterion for the fitted models were noted. One-way ANOVA and Tukey’s multiple comparison test were performed on these parameters. These models were evaluated based on the number of experimental trials generated in addition to the results of the statistical analyses. D-optimal design generated 12 trials in its model, which was lesser in comparison to both Central Composite and Box-Behnken designs. The R-square values of the fitted models were found to possess a statistically significant difference (P<0.0001). D-optimal design not only had the highest mean R-square value (0.7231), but also possessed the lowest means for both Akaike and Bayesian Information Criterion. The D-optimal design was recommended for generation of response surfaces, based on the assessment of the above parameters.

Optimal design of distributed control and embedded systems

CERN Document Server

Çela, Arben; Li, Xu-Guang; Niculescu, Silviu-Iulian

2014-01-01

Optimal Design of Distributed Control and Embedded Systems focuses on the design of special control and scheduling algorithms based on system structural properties as well as on analysis of the influence of induced time-delay on systems performances. It treats the optimal design of distributed and embedded control systems (DCESs) with respect to communication and calculation-resource constraints, quantization aspects, and potential time-delays induced by the associated  communication and calculation model. Particular emphasis is put on optimal control signal scheduling based on the system state. In order to render  this complex optimization problem feasible in real time, a time decomposition is based on periodicity induced by the static scheduling is operated. The authors present a co-design approach which subsumes the synthesis of the optimal control laws and the generation of an optimal schedule of control signals on real-time networks as well as the execution of control tasks on a single processor. The a...

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

Automated Design Framework for Synthetic Biology Exploiting Pareto Optimality.

Science.gov (United States)

Otero-Muras, Irene; Banga, Julio R

2017-07-21

In this work we consider Pareto optimality for automated design in synthetic biology. We present a generalized framework based on a mixed-integer dynamic optimization formulation that, given design specifications, allows the computation of Pareto optimal sets of designs, that is, the set of best trade-offs for the metrics of interest. We show how this framework can be used for (i) forward design, that is, finding the Pareto optimal set of synthetic designs for implementation, and (ii) reverse design, that is, analyzing and inferring motifs and/or design principles of gene regulatory networks from the Pareto set of optimal circuits. Finally, we illustrate the capabilities and performance of this framework considering four case studies. In the first problem we consider the forward design of an oscillator. In the remaining problems, we illustrate how to apply the reverse design approach to find motifs for stripe formation, rapid adaption, and fold-change detection, respectively.

PARAMETER COORDINATION AND ROBUST OPTIMIZATION FOR MULTIDISCIPLINARY DESIGN

Institute of Scientific and Technical Information of China (English)

HU Jie; PENG Yinghong; XIONG Guangleng

2006-01-01

A new parameter coordination and robust optimization approach for multidisciplinary design is presented. Firstly, the constraints network model is established to support engineering change, coordination and optimization. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. Secondly, the parameter coordination method is presented to solve the constraints network model, monitor the potential conflicts due to engineering changes, and obtain the consistency solution space corresponding to the given product specifications. Finally, the robust parameter optimization model is established, and genetic arithmetic is used to obtain the robust optimization parameter. An example of bogie design is analyzed to show the scheme to be effective.

New Methodology for Optimal Flight Control Using Differential Evolution Algorithms Applied on the Cessna Citation X Business Aircraft – Part 1. Design and Optimization

OpenAIRE

Yamina BOUGHARI; Georges GHAZI; Ruxandra Mihaela BOTEZ; Florian THEEL

2017-01-01

Setting the appropriate controllers for aircraft stability and control augmentation systems are complicated and time consuming tasks. As in the Linear Quadratic Regulator method gains are found by selecting the appropriate weights or as in the Proportional Integrator Derivative control by tuning gains. A trial and error process is usually employed for the determination of weighting matrices, which is normally a time consuming procedure. Flight Control Law were optimized and designed by combin...

Helium gas turbine conceptual design by genetic/gradient optimization

International Nuclear Information System (INIS)

Yang, Long; Yu, Suyuan

2003-01-01

Helium gas turbine is the key component of the power conversion system for direct cycle High Temperature Gas-cooled Reactors (HTGR), of which an optimal design is essential for high efficiency. Gas turbine design currently is a multidisciplinary process in which the relationships between constraints, objective functions and variables are very noisy. Due to the ever-increasing complexity of the process, it has becomes very hard for the engineering designer to foresee the consequences of changing certain parts. With classic design procedures which depend on adaptation to baseline design, this problem is usually averted by choosing a large number of design variables based on the engineer's judgment or experience in advance, then reaching a solution through iterative computation and modification. This, in fact, leads to a reduction of the degree of freedom of the design problem, and therefore to a suboptimal design. Furthermore, helium is very different in thermal properties from normal gases; it is uncertain whether the operation experiences of a normal gas turbine could be used in the conceptual design of a helium gas turbine. Therefore, it is difficult to produce an optimal design with the general method of adaptation to baseline. Since their appearance in the 1970s, Genetic algorithms (GAs) have been broadly used in many research fields due to their robustness. GAs have also been used recently in the design and optimization of turbo-machines. Researchers at the General Electronic Company (GE) developed an optimization software called Engineous, and used GAs in the basic design and optimization of turbines. The ITOP study group from Xi'an Transportation University also did some work on optimization of transonic turbine blades. However, since GAs do not have a rigorous theory base, many problems in utilities have arisen, such as premature convergence and uncertainty; the GA doesn't know how to locate the optimal design, and doesn't even know if the optimal solution

Evolutionary optimization methods for accelerator design

Science.gov (United States)

Poklonskiy, Alexey A.

Many problems from the fields of accelerator physics and beam theory can be formulated as optimization problems and, as such, solved using optimization methods. Despite growing efficiency of the optimization methods, the adoption of modern optimization techniques in these fields is rather limited. Evolutionary Algorithms (EAs) form a relatively new and actively developed optimization methods family. They possess many attractive features such as: ease of the implementation, modest requirements on the objective function, a good tolerance to noise, robustness, and the ability to perform a global search efficiently. In this work we study the application of EAs to problems from accelerator physics and beam theory. We review the most commonly used methods of unconstrained optimization and describe the GATool, evolutionary algorithm and the software package, used in this work, in detail. Then we use a set of test problems to assess its performance in terms of computational resources, quality of the obtained result, and the tradeoff between them. We justify the choice of GATool as a heuristic method to generate cutoff values for the COSY-GO rigorous global optimization package for the COSY Infinity scientific computing package. We design the model of their mutual interaction and demonstrate that the quality of the result obtained by GATool increases as the information about the search domain is refined, which supports the usefulness of this model. We Giscuss GATool's performance on the problems suffering from static and dynamic noise and study useful strategies of GATool parameter tuning for these and other difficult problems. We review the challenges of constrained optimization with EAs and methods commonly used to overcome them. We describe REPA, a new constrained optimization method based on repairing, in exquisite detail, including the properties of its two repairing techniques: REFIND and REPROPT. We assess REPROPT's performance on the standard constrained

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.

Commentary: considerations for using the 'Trials within Cohorts' design in a clinical trial of an investigational medicinal product.

Science.gov (United States)

Bibby, Anna C; Torgerson, David J; Leach, Samantha; Lewis-White, Helen; Maskell, Nick A

2018-01-08

The 'trials within cohorts' (TwiC) design is a pragmatic approach to randomised trials in which trial participants are randomly selected from an existing cohort. The design has multiple potential benefits, including the option of conducting multiple trials within the same cohort. To date, the TwiC design methodology been used in numerous clinical settings but has never been applied to a clinical trial of an investigational medicinal product (CTIMP). We have recently secured the necessary approvals to undertake the first CTIMP using the TwiC design. In this paper, we describe some of the considerations and modifications required to ensure such a trial is compliant with Good Clinical Practice and international clinical trials regulations. We advocate using a two-stage consent process and using the consent stages to explicitly differentiate between trial participants and cohort participants who are providing control data. This distinction ensured compliance but had consequences with respect to costings, recruitment and the trial assessment schedule. We have demonstrated that it is possible to secure ethical and regulatory approval for a CTIMP TwiC. By including certain considerations at the trial design stage, we believe this pragmatic and efficient methodology could be utilised in other CTIMPs in future.

SARCOPENIA: DESIGNING PHASE IIB TRIALS

Science.gov (United States)

CHUMLEA, WM.C.; CESARI, M.; EVANS, W.J.; FERRUCCI, L.; FIELDING, R.A.; PAHOR, M.; STUDENSKI, S.; VELLAS, B.

2012-01-01

Sarcopenia is the age-related involuntary loss of skeletal muscle mass and functionality that can lead to the development of disability, frailty and increased health care costs. The development of interventions aimed at preventing and/or treating sarcopenia is complex, requiring the adoption of assumptions and standards that are not well established scientifically or clinically. A number of investigators and clinicians (both from academia and industry) met in Rome (Italy) in 2009 to develop a consensus definition of sarcopenia. Subsequently, in Albuquerque (New Mexico, USA) in 2010, the same group met again to consider the complex issues necessary for designing Phase II clinical trials for sarcopenia. Current clinical trial data indicate that fat-free mass (FFM) parameters are responsive to physical activity/nutritional treatment modalities over short time periods, but pharmacological trials of sarcopenia have yet to show significant efficacy. In order to conduct a clinical trial within a reasonable time frame, groups that model or display accelerated aging and loss of FFM are necessary. Few studies have used acceptable designs for testing treatment effects, sample sizes or primary outcomes that could provide interpretable findings or effects across studies. Dual energy x ray absorptiometry (DXA) is the measure of choice for assessing FFM, but sufficient time is needed for changes to be detected accurately and reliably. A tool set that would allow clinical, basic and epidemiological research on sarcopenia to advance rapidly toward diagnosis and treatment phases should be those reflecting function and strength. PMID:21623466

Airfoil design and optimization

Energy Technology Data Exchange (ETDEWEB)

Lutz, T. [Stuttgart Univ. (Germany). Inst. fuer Aerodynamik und Gasdynamik

2001-07-01

The aerodynamic efficiency of mildly swept wings is mainly influenced by the characteristics of the airfoil sections. The specific design of airfoils is therefore one of the classical tasks of aerodynamics. Since the airfoil characteristics are directly dependent on the inviscid pressure distribution the application of inverse calculation methods is obvious. The direct numerical airfoil optimization offers an alternative to the manual design and attracts increasing interest. (orig.)

Comparison of Traditional Design Nonlinear Programming Optimization and Stochastic Methods for Structural Design

Science.gov (United States)

Patnaik, Surya N.; Pai, Shantaram S.; Coroneos, Rula M.

2010-01-01

Structural design generated by traditional method, optimization method and the stochastic design concept are compared. In the traditional method, the constraints are manipulated to obtain the design and weight is back calculated. In design optimization, the weight of a structure becomes the merit function with constraints imposed on failure modes and an optimization algorithm is used to generate the solution. Stochastic design concept accounts for uncertainties in loads, material properties, and other parameters and solution is obtained by solving a design optimization problem for a specified reliability. Acceptable solutions were produced by all the three methods. The variation in the weight calculated by the methods was modest. Some variation was noticed in designs calculated by the methods. The variation may be attributed to structural indeterminacy. It is prudent to develop design by all three methods prior to its fabrication. The traditional design method can be improved when the simplified sensitivities of the behavior constraint is used. Such sensitivity can reduce design calculations and may have a potential to unify the traditional and optimization methods. Weight versus reliabilitytraced out an inverted-S-shaped graph. The center of the graph corresponded to mean valued design. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure. Weight can be reduced to a small value for a most failure-prone design. Probabilistic modeling of load and material properties remained a challenge.

New approaches to optimization in aerospace conceptual design

Science.gov (United States)

Gage, Peter J.

1995-01-01

Aerospace design can be viewed as an optimization process, but conceptual studies are rarely performed using formal search algorithms. Three issues that restrict the success of automatic search are identified in this work. New approaches are introduced to address the integration of analyses and optimizers, to avoid the need for accurate gradient information and a smooth search space (required for calculus-based optimization), and to remove the restrictions imposed by fixed complexity problem formulations. (1) Optimization should be performed in a flexible environment. A quasi-procedural architecture is used to conveniently link analysis modules and automatically coordinate their execution. It efficiently controls a large-scale design tasks. (2) Genetic algorithms provide a search method for discontinuous or noisy domains. The utility of genetic optimization is demonstrated here, but parameter encodings and constraint-handling schemes must be carefully chosen to avoid premature convergence to suboptimal designs. The relationship between genetic and calculus-based methods is explored. (3) A variable-complexity genetic algorithm is created to permit flexible parameterization, so that the level of description can change during optimization. This new optimizer automatically discovers novel designs in structural and aerodynamic tasks.

Systematic design of microstructures by topology optimization

DEFF Research Database (Denmark)

Sigmund, Ole

2003-01-01

The topology optimization method can be used to determine the material distribution in a design domain such that an objective function is maximized and constraints are fulfilled. The method which is based on Finite Element Analysis may be applied to all kinds of material distribution problems like...... extremal material design, sensor and actuator design and MEMS synthesis. The state-of-the-art in topology optimization will be reviewed and older as well as new applications in phononic and photonic crystals design will be presented....

Poly-optimization: a paradigm in engineering design in mechatronics

Energy Technology Data Exchange (ETDEWEB)

Tarnowski, Wojciech [Koszalin University of Technology, Department of Control and Driving Systems, Institute of Mechatronics, Nanotechnology and Vacuum Technique, Koszalin (Poland); Krzyzynski, Tomasz; Maciejewski, Igor; Oleskiewicz, Robert [Koszalin University of Technology, Department of Mechatronics and Applied Mechanics, Institute of Mechatronics, Nanotechnology and Vacuum Technique, Koszalin (Poland)

2011-02-15

The paper deals with the Engineering Design that is a general methodology of a design process. It is assumed that a designer has to solve a design task as an inverse problem in an iterative way. After each iteration, a decision should be taken on the information that is called a centre of integration in a systematic design system. For this purpose, poly-optimal solutions may be used. The poly-optimization is presented and contrasted against the Multi Attribute Decision Making, and a set of the poly-optimal solutions is defined. Then Mechatronics is defined and its characteristics given, to prove that mechatronic design process vitally needs CAD tools. Three examples are quoted to demonstrate a key role of the poly-optimization in the mechatronic design. (orig.)

Improving hypertension management through pharmacist prescribing; the rural alberta clinical trial in optimizing hypertension (Rural RxACTION: trial design and methods

Directory of Open Access Journals (Sweden)

Campbell Norman RC

2011-08-01

Full Text Available Abstract Background Patients with hypertension continue to have less than optimal blood pressure control, with nearly one in five Canadian adults having hypertension. Pharmacist prescribing is gaining favor as a potential clinically efficacious and cost-effective means to improve both access and quality of care. With Alberta being the first province in Canada to have independent prescribing by pharmacists, it offers a unique opportunity to evaluate outcomes in patients who are prescribed antihypertensive therapy by pharmacists. Methods The study is a randomized controlled trial of enhanced pharmacist care, with the unit of randomization being the patient. Participants will be randomized to enhanced pharmacist care (patient identification, assessment, education, close follow-up, and prescribing/titration of antihypertensive medications or usual care. Participants are patients in rural Alberta with undiagnosed/uncontrolled blood pressure, as defined by the Canadian Hypertension Education Program. The primary outcome is the change in systolic blood pressure between baseline and 24 weeks in the enhanced-care versus usual-care arms. There are also three substudies running in conjunction with the project examining different remuneration models, investigating patient knowledge, and assessing health-resource utilization amongst patients in each group. Discussion To date, one-third of the required sample size has been recruited. There are 15 communities and 17 pharmacists actively screening, recruiting, and following patients. This study will provide high-level evidence regarding pharmacist prescribing. Trial Registration Clinicaltrials.gov NCT00878566.

Design and Optimization Method of a Two-Disk Rotor System

Science.gov (United States)

Huang, Jingjing; Zheng, Longxi; Mei, Qing

2016-04-01

An integrated analytical method based on multidisciplinary optimization software Isight and general finite element software ANSYS was proposed in this paper. Firstly, a two-disk rotor system was established and the mode, humorous response and transient response at acceleration condition were analyzed with ANSYS. The dynamic characteristics of the two-disk rotor system were achieved. On this basis, the two-disk rotor model was integrated to the multidisciplinary design optimization software Isight. According to the design of experiment (DOE) and the dynamic characteristics, the optimization variables, optimization objectives and constraints were confirmed. After that, the multi-objective design optimization of the transient process was carried out with three different global optimization algorithms including Evolutionary Optimization Algorithm, Multi-Island Genetic Algorithm and Pointer Automatic Optimizer. The optimum position of the two-disk rotor system was obtained at the specified constraints. Meanwhile, the accuracy and calculation numbers of different optimization algorithms were compared. The optimization results indicated that the rotor vibration reached the minimum value and the design efficiency and quality were improved by the multidisciplinary design optimization in the case of meeting the design requirements, which provided the reference to improve the design efficiency and reliability of the aero-engine rotor.

Embracing model-based designs for dose-finding trials.

Science.gov (United States)

Love, Sharon B; Brown, Sarah; Weir, Christopher J; Harbron, Chris; Yap, Christina; Gaschler-Markefski, Birgit; Matcham, James; Caffrey, Louise; McKevitt, Christopher; Clive, Sally; Craddock, Charlie; Spicer, James; Cornelius, Victoria

2017-07-25

Dose-finding trials are essential to drug development as they establish recommended doses for later-phase testing. We aim to motivate wider use of model-based designs for dose finding, such as the continual reassessment method (CRM). We carried out a literature review of dose-finding designs and conducted a survey to identify perceived barriers to their implementation. We describe the benefits of model-based designs (flexibility, superior operating characteristics, extended scope), their current uptake, and existing resources. The most prominent barriers to implementation of a model-based design were lack of suitable training, chief investigators' preference for algorithm-based designs (e.g., 3+3), and limited resources for study design before funding. We use a real-world example to illustrate how these barriers can be overcome. There is overwhelming evidence for the benefits of CRM. Many leading pharmaceutical companies routinely implement model-based designs. Our analysis identified barriers for academic statisticians and clinical academics in mirroring the progress industry has made in trial design. Unified support from funders, regulators, and journal editors could result in more accurate doses for later-phase testing, and increase the efficiency and success of clinical drug development. We give recommendations for increasing the uptake of model-based designs for dose-finding trials in academia.

Multi-objective optimization design method of radiation shielding

International Nuclear Information System (INIS)

Yang Shouhai; Wang Weijin; Lu Daogang; Chen Yixue

2012-01-01

Due to the shielding design goals of diversification and uncertain process of many factors, it is necessary to develop an optimization design method of intelligent shielding by which the shielding scheme selection will be achieved automatically and the uncertainties of human impact will be reduced. For economical feasibility to achieve a radiation shielding design for automation, the multi-objective genetic algorithm optimization of screening code which combines the genetic algorithm and discrete-ordinate method was developed to minimize the costs, size, weight, and so on. This work has some practical significance for gaining the optimization design of shielding. (authors)

Simple heuristics: A bridge between manual core design and automated optimization methods

International Nuclear Information System (INIS)

White, J.R.; Delmolino, P.M.

1993-01-01

The primary function of RESCUE is to serve as an aid in the analysis and identification of feasible loading patterns for LWR reload cores. The unique feature of RESCUE is that its physics model is based on some recent advances in generalized perturbation theory (GPT) methods. The high order GPT techniques offer the accuracy, computational efficiency, and flexibility needed for the implementation of a full range of capabilities within a set of compatible interactive (manual and semi-automated) and automated design tools. The basic design philosophy and current features within RESCUE are reviewed, and the new semi-automated capability is highlighted. The online advisor facility appears quite promising and it provides a natural bridge between the traditional trial-and-error manual process and the recent progress towards fully automated optimization sequences. (orig.)

Design optimization of grid-connected PV inverters

DEFF Research Database (Denmark)

Koutroulis, Eftichios; Blaabjerg, Frede

2011-01-01

The DC/AC inverters are the key elements in grid-connected PV energy production systems. In this paper, new design optimization techniques focused on transformerless (very high efficiency) PV inverters are proposed. They have been developed based on an analysis of the deficiencies of the current......, state-of-the-art PV inverters design technology, which limits the amount of PV energy supplied into the electric grid. The influences of the electric grid regulations and standards and the PV array operational characteristics on the design of grid-connected PV inverters have also been considered....... The simulation results verify that the proposed optimization techniques enable the maximization of the PV energy injected into the electric grid by the optimized PV installation....

Concurrent Aeroservoelastic Design and Optimization of Wind Turbines

DEFF Research Database (Denmark)

Tibaldi, Carlo

This work develops and investigates methods to integrate controllers in the wind turbine design process and to perform wind turbine optimization. These techniques can exploit the synergy between wind turbine components and generate new design solutions. Two frameworks to perform wind turbine...... optimization design are presented. These tools handle workflows to model a wind turbine and to evaluate loads and performances under specific conditions. Three approaches to evaluate loads are proposed and integrated in the optimization codes. The first method is based on time domain simulations, the second...... simulations, allows the selection of any controller parameter. The methods to evaluate loads and the pole-placement technique are then employed to carry out wind turbine optimization design from an aeroservoelastic prospective. Several analysis of the NREL 5 MW Reference Wind Turbine and the DTU 10 MW...

Models and Methods for Structural Topology Optimization with Discrete Design Variables

DEFF Research Database (Denmark)

Stolpe, Mathias

in the conceptual design phase to find innovative designs. The strength of topology optimization is the capability of determining both the optimal shape and the topology of the structure. In some cases also the optimal material properties can be determined. Optimal structural design problems are modeled...... such as bridges, airplanes, wind turbines, cars, etc. Topology optimization is a collection of theory, mathematical models, and numerical methods and is often used in the conceptual design phase to find innovative designs. The strength of topology optimization is the capability of determining both the optimal......Structural topology optimization is a multi-disciplinary research field covering optimal design of load carrying mechanical structures such as bridges, airplanes, wind turbines, cars, etc. Topology optimization is a collection of theory, mathematical models, and numerical methods and is often used...

Dynamic optimization and adaptive controller design

Science.gov (United States)

Inamdar, S. R.

2010-10-01

In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.

Ground Vehicle System Integration (GVSI) and Design Optimization Model

National Research Council Canada - National Science Library

Horton, William

1996-01-01

This report documents the Ground Vehicle System Integration (GVSI) and Design Optimization Model GVSI is a top-level analysis tool designed to support engineering tradeoff studies and vehicle design optimization efforts...

Genetic algorithms applied to nuclear reactor design optimization

International Nuclear Information System (INIS)

Pereira, C.M.N.A.; Schirru, R.; Martinez, A.S.

2000-01-01

A genetic algorithm is a powerful search technique that simulates natural evolution in order to fit a population of computational structures to the solution of an optimization problem. This technique presents several advantages over classical ones such as linear programming based techniques, often used in nuclear engineering optimization problems. However, genetic algorithms demand some extra computational cost. Nowadays, due to the fast computers available, the use of genetic algorithms has increased and its practical application has become a reality. In nuclear engineering there are many difficult optimization problems related to nuclear reactor design. Genetic algorithm is a suitable technique to face such kind of problems. This chapter presents applications of genetic algorithms for nuclear reactor core design optimization. A genetic algorithm has been designed to optimize the nuclear reactor cell parameters, such as array pitch, isotopic enrichment, dimensions and cells materials. Some advantages of this genetic algorithm implementation over a classical method based on linear programming are revealed through the application of both techniques to a simple optimization problem. In order to emphasize the suitability of genetic algorithms for design optimization, the technique was successfully applied to a more complex problem, where the classical method is not suitable. Results and comments about the applications are also presented. (orig.)

Transportation package design using numerical optimization

International Nuclear Information System (INIS)

Harding, D.C.; Witkowski, W.R.

1993-01-01

Since the design of transportation packages involves a complex coupling of structural, thermal and radiation shielding analyses and must follow very strict design constraints, numerical optimization provides the potential for more efficient container designs. In numerical optimization, the requirements of the design problem are mathematically formulated through the use of an objective function and constraints. The objective function(s), e.g., package weight, cost, volume, or combination thereof, is the function to be minimized or maximized by altering a set of design variables that define the package's shape and dimensions. Constraints are limitations on the performance of the system, such as resisting structural and thermal accident environments. Two constraints defined for an example wire mesh composite Type B package are: 1) deformation in the containment vessel seal region remains small enough throughout the 10 CFR-71 accident conditions to meet containment criteria, and 2) the elastomeric seal region remains below its operational temperature limit to guarantee seal integrity in the fire environment. The first constraint of a minimum energy absorbing layer thickness is evaluated with finite element analyses of the proposed dynamic crush accident criteria. The second constraint is evaluated with a 1-D transient thermal finite difference code parametrized for variable composite layer thicknesses, and is integrated with the optimization process. (J.P.N.)

Optimizing clinical trial supply requirements: simulation of computer-controlled supply chain management.

Science.gov (United States)

Peterson, Magnus; Byrom, Bill; Dowlman, Nikki; McEntegart, Damian

2004-01-01

Computer-controlled systems are commonly used in clinical trials to control dispensing and manage site inventories of trial supplies. Typically such systems are used with an interactive telephone or web system that provide an interface with the study site. Realizing the maximum savings in medication associated with this approach has, in the past, been problematic as it has been difficult to fully estimate medication requirements due to the complexities of these algorithms and the inherent variation in the clinical trial recruitment process. We describe the traditional and automated methods of supplying sites. We detail a simulation approach that models the automated system. We design a number of simulation experiments using this model to investigate the supply strategy properties that influence medication overage and other strategy performance metrics. The computer-controlled medication system gave superior performance to the traditional method. In one example, a 75% overage of wasted medication in the traditional system was associated with higher supply failure than an automated system strategy with an overage of 47%. In a further example, we demonstrate that the impact of using a country stratified as opposed to site stratified scheme affects the number of deliveries and probability of supply failures more than the amount of drug wasted with respective increases of 20, 2300 and 4%. Medication savings with automated systems are particularly significant in repeat dispensing designs. We show that the number of packs required can fall by as much as 50% if one uses a predictive medication algorithm. We conclude that a computer-controlled supply chain enables medication savings to be realized and that it is possible to quantify the distribution of these savings using a simulation model. The simulation model can be used to optimize the prestudy medication supply strategy and for midstudy monitoring using real-time data contained in the study database.

Acoustic design by topology optimization

DEFF Research Database (Denmark)

Dühring, Maria Bayard; Jensen, Jakob Søndergaard; Sigmund, Ole

2008-01-01

To bring down noise levels in human surroundings is an important issue and a method to reduce noise by means of topology optimization is presented here. The acoustic field is modeled by Helmholtz equation and the topology optimization method is based on continuous material interpolation functions...... in the density and bulk modulus. The objective function is the squared sound pressure amplitude. First, room acoustic problems are considered and it is shown that the sound level can be reduced in a certain part of the room by an optimized distribution of reflecting material in a design domain along the ceiling...

Optimal Pid Controller Design Using Adaptive Vurpso Algorithm

Science.gov (United States)

Zirkohi, Majid Moradi

2015-04-01

The purpose of this paper is to improve theVelocity Update Relaxation Particle Swarm Optimization algorithm (VURPSO). The improved algorithm is called Adaptive VURPSO (AVURPSO) algorithm. Then, an optimal design of a Proportional-Integral-Derivative (PID) controller is obtained using the AVURPSO algorithm. An adaptive momentum factor is used to regulate a trade-off between the global and the local exploration abilities in the proposed algorithm. This operation helps the system to reach the optimal solution quickly and saves the computation time. Comparisons on the optimal PID controller design confirm the superiority of AVURPSO algorithm to the optimization algorithms mentioned in this paper namely the VURPSO algorithm, the Ant Colony algorithm, and the conventional approach. Comparisons on the speed of convergence confirm that the proposed algorithm has a faster convergence in a less computation time to yield a global optimum value. The proposed AVURPSO can be used in the diverse areas of optimization problems such as industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning. The proposed AVURPSO algorithm is efficiently used to design an optimal PID controller.

Optimal Design of Modern Transformerless PV Inverter Topologies

DEFF Research Database (Denmark)

Saridakis, Stefanos; Koutroulis, Eftichios; Blaabjerg, Frede

2013-01-01

the operational lifetime period of the PV installation, is also considered in the optimization process. According to the results of the proposed design method, different optimal values of the PV inverter design variables are derived for each PV inverter topology and installation site. The H5, H6, neutral point...... clamped, active-neutral point clamped and conergy-NPC PV inverters designed using the proposed optimization process feature lower levelized cost of generated electricity and lifetime cost, longer mean time between failures and inject more PV-generated energy into the electric grid than their nonoptimized......The design optimization of H5, H6, neutral point clamped, active-neutral point clamped, and conergy-NPC transformerless photovoltaic (PV) inverters is presented in this paper. The components reliability in terms of the corresponding malfunctions, affecting the PV inverter maintenance cost during...

Regression analysis as a design optimization tool

Science.gov (United States)

Perley, R.

1984-01-01

The optimization concepts are described in relation to an overall design process as opposed to a detailed, part-design process where the requirements are firmly stated, the optimization criteria are well established, and a design is known to be feasible. The overall design process starts with the stated requirements. Some of the design criteria are derived directly from the requirements, but others are affected by the design concept. It is these design criteria that define the performance index, or objective function, that is to be minimized within some constraints. In general, there will be multiple objectives, some mutually exclusive, with no clear statement of their relative importance. The optimization loop that is given adjusts the design variables and analyzes the resulting design, in an iterative fashion, until the objective function is minimized within the constraints. This provides a solution, but it is only the beginning. In effect, the problem definition evolves as information is derived from the results. It becomes a learning process as we determine what the physics of the system can deliver in relation to the desirable system characteristics. As with any learning process, an interactive capability is a real attriubute for investigating the many alternatives that will be suggested as learning progresses.

Multidisciplinary Analysis and Optimal Design: As Easy as it Sounds?

Science.gov (United States)

Moore, Greg; Chainyk, Mike; Schiermeier, John

2004-01-01

The viewgraph presentation examines optimal design for precision, large aperture structures. Discussion focuses on aspects of design optimization, code architecture and current capabilities, and planned activities and collaborative area suggestions. The discussion of design optimization examines design sensitivity analysis; practical considerations; and new analytical environments including finite element-based capability for high-fidelity multidisciplinary analysis, design sensitivity, and optimization. The discussion of code architecture and current capabilities includes basic thermal and structural elements, nonlinear heat transfer solutions and process, and optical modes generation.

Design and optimization of thermoacoustic devices

International Nuclear Information System (INIS)

Babaei, Hadi; Siddiqui, Kamran

2008-01-01

Thermoacoustics deals with the conversion of heat energy into sound energy and vice versa. It is a new and emerging technology which has a strong potential towards the development of sustainable and renewable energy systems by utilizing waste heat or solar energy. Although simple to fabricate, the designing of thermoacoustic devices is very challenging. In the present study, a comprehensive design and optimization algorithm is developed for designing thermoacoustic devices. The unique feature of the present algorithm is its ability to design thermoacoustically-driven thermoacoustic refrigerators that can serve as sustainable refrigeration systems. In addition, new features based on the energy balance are also included to design individual thermoacoustic engines and acoustically-driven thermoacoustic refrigerators. As a case study, a thermoacoustically-driven thermoacoustic refrigerator has been designed and optimized based on the developed algorithm. The results from the algorithm are in good agreement with that obtained from the computer code DeltaE

Optimal design of water supply networks for enhancing seismic reliability

International Nuclear Information System (INIS)

Yoo, Do Guen; Kang, Doosun; Kim, Joong Hoon

2016-01-01

The goal of the present study is to construct a reliability evaluation model of a water supply system taking seismic hazards and present techniques to enhance hydraulic reliability of the design into consideration. To maximize seismic reliability with limited budgets, an optimal design model is developed using an optimization technique called harmony search (HS). The model is applied to actual water supply systems to determine pipe diameters that can maximize seismic reliability. The reliabilities between the optimal design and existing designs were compared and analyzed. The optimal design would both enhance reliability by approximately 8.9% and have a construction cost of approximately 1.3% less than current pipe construction cost. In addition, the reinforcement of the durability of individual pipes without considering the system produced ineffective results in terms of both cost and reliability. Therefore, to increase the supply ability of the entire system, optimized pipe diameter combinations should be derived. Systems in which normal status hydraulic stability and abnormal status available demand could be maximally secured if configured through the optimal design. - Highlights: • We construct a seismic reliability evaluation model of water supply system. • We present technique to enhance hydraulic reliability in the aspect of design. • Harmony search algorithm is applied in optimal designs process. • The effects of the proposed optimal design are improved reliability about by 9%. • Optimized pipe diameter combinations should be derived indispensably.

Systematic design of acoustic devices by topology optimization

DEFF Research Database (Denmark)

Jensen, Jakob Søndergaard; Sigmund, Ole

2005-01-01

We present a method to design acoustic devices with topology optimization. The general algorithm is exemplified by the design of a reflection chamber that minimizes the transmission of acoustic waves in a specified frequency range.......We present a method to design acoustic devices with topology optimization. The general algorithm is exemplified by the design of a reflection chamber that minimizes the transmission of acoustic waves in a specified frequency range....

Integrated Reliability-Based Optimal Design of Structures

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Thoft-Christensen, Palle

1987-01-01

In conventional optimal design of structural systems the weight or the initial cost of the structure is usually used as objective function. Further, the constraints require that the stresses and/or strains at some critical points have to be less than some given values. Finally, all variables......-based optimal design is discussed. Next, an optimal inspection and repair strategy for existing structural systems is presented. An optimization problem is formulated , where the objective is to minimize the expected total future cost of inspection and repair subject to the constraint that the reliability...... value. The reliability can be measured from an element and/or a systems point of view. A number of methods to solve reliability-based optimization problems has been suggested, see e.g. Frangopol [I]. Murotsu et al. (2], Thoft-Christensen & Sørensen (3] and Sørensen (4). For structures where...

GPU-accelerated CFD Simulations for Turbomachinery Design Optimization

NARCIS (Netherlands)

Aissa, M.H.

2017-01-01

Design optimization relies heavily on time-consuming simulations, especially when using gradient-free optimization methods. These methods require a large number of simulations in order to get a remarkable improvement over reference designs, which are nowadays based on the accumulated engineering

Controller Design Automation for Aeroservoelastic Design Optimization of Wind Turbines

NARCIS (Netherlands)

Ashuri, T.; Van Bussel, G.J.W.; Zaayer, M.B.; Van Kuik, G.A.M.

2010-01-01

The purpose of this paper is to integrate the controller design of wind turbines with structure and aerodynamic analysis and use the final product in the design optimization process (DOP) of wind turbines. To do that, the controller design is automated and integrated with an aeroelastic simulation

The Potential Role of Cache Mechanism for Complicated Design Optimization

International Nuclear Information System (INIS)

Noriyasu, Hirokawa; Fujita, Kikuo

2002-01-01

This paper discusses the potential role of cache mechanism for complicated design optimization While design optimization is an application of mathematical programming techniques to engineering design problems over numerical computation, its progress has been coevolutionary. The trend in such progress indicates that more complicated applications become the next target of design optimization beyond growth of computational resources. As the progress in the past two decades had required response surface techniques, decomposition techniques, etc., any new framework must be introduced for the future of design optimization methods. This paper proposes a possibility of what we call cache mechanism for mediating the coming challenge and briefly demonstrates some promises in the idea of Voronoi diagram based cumulative approximation as an example of its implementation, development of strict robust design, extension of design optimization for product variety

Topology Optimization - Engineering Contribution to Architectural Design

Science.gov (United States)

Tajs-Zielińska, Katarzyna; Bochenek, Bogdan

2017-10-01

The idea of the topology optimization is to find within a considered design domain the distribution of material that is optimal in some sense. Material, during optimization process, is redistributed and parts that are not necessary from objective point of view are removed. The result is a solid/void structure, for which an objective function is minimized. This paper presents an application of topology optimization to multi-material structures. The design domain defined by shape of a structure is divided into sub-regions, for which different materials are assigned. During design process material is relocated, but only within selected region. The proposed idea has been inspired by architectural designs like multi-material facades of buildings. The effectiveness of topology optimization is determined by proper choice of numerical optimization algorithm. This paper utilises very efficient heuristic method called Cellular Automata. Cellular Automata are mathematical, discrete idealization of a physical systems. Engineering implementation of Cellular Automata requires decomposition of the design domain into a uniform lattice of cells. It is assumed, that the interaction between cells takes place only within the neighbouring cells. The interaction is governed by simple, local update rules, which are based on heuristics or physical laws. The numerical studies show, that this method can be attractive alternative to traditional gradient-based algorithms. The proposed approach is evaluated by selected numerical examples of multi-material bridge structures, for which various material configurations are examined. The numerical studies demonstrated a significant influence the material sub-regions location on the final topologies. The influence of assumed volume fraction on final topologies for multi-material structures is also observed and discussed. The results of numerical calculations show, that this approach produces different results as compared with classical one

Topology optimization problems with design-dependent sets of constraints

DEFF Research Database (Denmark)

Schou, Marie-Louise Højlund

Topology optimization is a design tool which is used in numerous fields. It can be used whenever the design is driven by weight and strength considerations. The basic concept of topology optimization is the interpretation of partial differential equation coefficients as effective material...... properties and designing through changing these coefficients. For example, consider a continuous structure. Then the basic concept is to represent this structure by small pieces of material that are coinciding with the elements of a finite element model of the structure. This thesis treats stress constrained...... structural topology optimization problems. For such problems a stress constraint for an element should only be present in the optimization problem when the structural design variable corresponding to this element has a value greater than zero. We model the stress constrained topology optimization problem...

Big Data in Designing Clinical Trials: Opportunities and Challenges.

Science.gov (United States)

Mayo, Charles S; Matuszak, Martha M; Schipper, Matthew J; Jolly, Shruti; Hayman, James A; Ten Haken, Randall K

2017-01-01

Emergence of big data analytics resource systems (BDARSs) as a part of routine practice in Radiation Oncology is on the horizon. Gradually, individual researchers, vendors, and professional societies are leading initiatives to create and demonstrate use of automated systems. What are the implications for design of clinical trials, as these systems emerge? Gold standard, randomized controlled trials (RCTs) have high internal validity for the patients and settings fitting constraints of the trial, but also have limitations including: reproducibility, generalizability to routine practice, infrequent external validation, selection bias, characterization of confounding factors, ethics, and use for rare events. BDARS present opportunities to augment and extend RCTs. Preliminary modeling using single- and muti-institutional BDARS may lead to better design and less cost. Standardizations in data elements, clinical processes, and nomenclatures used to decrease variability and increase veracity needed for automation and multi-institutional data pooling in BDARS also support ability to add clinical validation phases to clinical trial design and increase participation. However, volume and variety in BDARS present other technical, policy, and conceptual challenges including applicable statistical concepts, cloud-based technologies. In this summary, we will examine both the opportunities and the challenges for use of big data in design of clinical trials.

Big Data in Designing Clinical Trials: Opportunities and Challenges

Directory of Open Access Journals (Sweden)

Charles S. Mayo

2017-08-01

Full Text Available Emergence of big data analytics resource systems (BDARSs as a part of routine practice in Radiation Oncology is on the horizon. Gradually, individual researchers, vendors, and professional societies are leading initiatives to create and demonstrate use of automated systems. What are the implications for design of clinical trials, as these systems emerge? Gold standard, randomized controlled trials (RCTs have high internal validity for the patients and settings fitting constraints of the trial, but also have limitations including: reproducibility, generalizability to routine practice, infrequent external validation, selection bias, characterization of confounding factors, ethics, and use for rare events. BDARS present opportunities to augment and extend RCTs. Preliminary modeling using single- and muti-institutional BDARS may lead to better design and less cost. Standardizations in data elements, clinical processes, and nomenclatures used to decrease variability and increase veracity needed for automation and multi-institutional data pooling in BDARS also support ability to add clinical validation phases to clinical trial design and increase participation. However, volume and variety in BDARS present other technical, policy, and conceptual challenges including applicable statistical concepts, cloud-based technologies. In this summary, we will examine both the opportunities and the challenges for use of big data in design of clinical trials.

Software for CATV Design and Frequency Plan Optimization

OpenAIRE

Hala, O.

2007-01-01

The paper deals with the structure of a software medium used for design and sub-optimization of frequency plan in CATV networks, their description and design method. The software performance is described and a simple design example of energy balance of a simplified CATV network is given. The software was created in programming environment called Delphi and local optimization was made in Matlab.

Analog Circuit Design Optimization Based on Evolutionary Algorithms

Directory of Open Access Journals (Sweden)

Mansour Barari

2014-01-01

Full Text Available This paper investigates an evolutionary-based designing system for automated sizing of analog integrated circuits (ICs. Two evolutionary algorithms, genetic algorithm and PSO (Parswal particle swarm optimization algorithm, are proposed to design analog ICs with practical user-defined specifications. On the basis of the combination of HSPICE and MATLAB, the system links circuit performances, evaluated through specific electrical simulation, to the optimization system in the MATLAB environment, for the selected topology. The system has been tested by typical and hard-to-design cases, such as complex analog blocks with stringent design requirements. The results show that the design specifications are closely met. Comparisons with available methods like genetic algorithms show that the proposed algorithm offers important advantages in terms of optimization quality and robustness. Moreover, the algorithm is shown to be efficient.

Improving Battery Reactor Core Design Using Optimization Method

International Nuclear Information System (INIS)

Son, Hyung M.; Suh, Kune Y.

2011-01-01

The Battery Omnibus Reactor Integral System (BORIS) is a small modular fast reactor being designed at Seoul National University to satisfy various energy demands, to maintain inherent safety by liquid-metal coolant lead for natural circulation heat transport, and to improve power conversion efficiency with the Modular Optimal Balance Integral System (MOBIS) using the supercritical carbon dioxide as working fluid. This study is focused on developing the Neutronics Optimized Reactor Analysis (NORA) method that can quickly generate conceptual design of a battery reactor core by means of first principle calculations, which is part of the optimization process for reactor assembly design of BORIS

Series: Pragmatic trials and real world evidence: Paper 1. Introduction.

Science.gov (United States)

Zuidgeest, Mira G P; Goetz, Iris; Groenwold, Rolf H H; Irving, Elaine; van Thiel, Ghislaine J M W; Grobbee, Diederick E

2017-08-01

This is the introductory paper in a series of eight papers. In this series, we integrate the theoretical design options with the practice of conducting pragmatic trials. For most new market-approved treatments, the clinical evidence is insufficient to fully guide physicians and policy makers in choosing the optimal treatment for their patients. Pragmatic trials can fill this gap, by providing evidence on the relative effectiveness of a treatment strategy in routine clinical practice, already in an early phase of development, while maintaining the strength of randomized controlled trials. Selecting the setting, study population, mode of intervention, comparator, and outcome are crucial in designing pragmatic trials. In combination with monitoring and data collection that does not change routine care, this will enable appropriate generalization to the target patient group in clinical practice. To benefit from the full potential of pragmatic trials, there is a need for guidance and tools in designing these studies while ensuring operational feasibility. This paper introduces the concept of pragmatic trial design. The complex interplay between pragmatic design options, feasibility, stakeholder acceptability, validity, precision, and generalizability will be clarified. In this way, balanced design choices can be made in pragmatic trials with an optimal chance of success in practice. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Optimizing trial design in pharmacogenetics research: comparing a fixed parallel group, group sequential, and adaptive selection design on sample size requirements.

Science.gov (United States)

Boessen, Ruud; van der Baan, Frederieke; Groenwold, Rolf; Egberts, Antoine; Klungel, Olaf; Grobbee, Diederick; Knol, Mirjam; Roes, Kit

2013-01-01

Two-stage clinical trial designs may be efficient in pharmacogenetics research when there is some but inconclusive evidence of effect modification by a genomic marker. Two-stage designs allow to stop early for efficacy or futility and can offer the additional opportunity to enrich the study population to a specific patient subgroup after an interim analysis. This study compared sample size requirements for fixed parallel group, group sequential, and adaptive selection designs with equal overall power and control of the family-wise type I error rate. The designs were evaluated across scenarios that defined the effect sizes in the marker positive and marker negative subgroups and the prevalence of marker positive patients in the overall study population. Effect sizes were chosen to reflect realistic planning scenarios, where at least some effect is present in the marker negative subgroup. In addition, scenarios were considered in which the assumed 'true' subgroup effects (i.e., the postulated effects) differed from those hypothesized at the planning stage. As expected, both two-stage designs generally required fewer patients than a fixed parallel group design, and the advantage increased as the difference between subgroups increased. The adaptive selection design added little further reduction in sample size, as compared with the group sequential design, when the postulated effect sizes were equal to those hypothesized at the planning stage. However, when the postulated effects deviated strongly in favor of enrichment, the comparative advantage of the adaptive selection design increased, which precisely reflects the adaptive nature of the design. Copyright © 2013 John Wiley & Sons, Ltd.

Optimal design of RTCs in digital circuit fault self-repair based on global signal optimization

Institute of Scientific and Technical Information of China (English)

Zhang Junbin; Cai Jinyan; Meng Yafeng

2016-01-01

Since digital circuits have been widely and thoroughly applied in various fields, electronic systems are increasingly more complicated and require greater reliability. Faults may occur in elec-tronic systems in complicated environments. If immediate field repairs are not made on the faults, elec-tronic systems will not run normally, and this will lead to serious losses. The traditional method for improving system reliability based on redundant fault-tolerant technique has been unable to meet the requirements. Therefore, on the basis of (evolvable hardware)-based and (reparation balance technology)-based electronic circuit fault self-repair strategy proposed in our preliminary work, the optimal design of rectification circuits (RTCs) in electronic circuit fault self-repair based on global sig-nal optimization is deeply researched in this paper. First of all, the basic theory of RTC optimal design based on global signal optimization is proposed. Secondly, relevant considerations and suitable ranges are analyzed. Then, the basic flow of RTC optimal design is researched. Eventually, a typical circuit is selected for simulation verification, and detailed simulated analysis is made on five circumstances that occur during RTC evolution. The simulation results prove that compared with the conventional design method based RTC, the global signal optimization design method based RTC is lower in hardware cost, faster in circuit evolution, higher in convergent precision, and higher in circuit evolution success rate. Therefore, the global signal optimization based RTC optimal design method applied in the elec-tronic circuit fault self-repair technology is proven to be feasible, effective, and advantageous.

Research design considerations for single-dose analgesic clinical trials in acute pain

DEFF Research Database (Denmark)

Cooper, Stephen A; Desjardins, Paul J; Turk, Dennis C

2016-01-01

This article summarizes the results of a meeting convened by the Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) on key considerations and best practices governing the design of acute pain clinical trials. We discuss the role of early phase clinical trials......, including pharmacokinetic-pharmacodynamic (PK-PD) trials, and the value of including both placebo and active standards of comparison in acute pain trials. This article focuses on single-dose and short-duration trials with emphasis on the perioperative and study design factors that influence assay...... sensitivity. Recommendations are presented on assessment measures, study designs, and operational factors. Although most of the methodological advances have come from studies of postoperative pain after dental impaction, bunionectomy, and other surgeries, the design considerations discussed are applicable...

Design optimization of jacket structures for mass production

DEFF Research Database (Denmark)

Sandal, Kasper

This thesis presents models and applications for structural optimization of jacket structures for offshore wind turbines. The motivation is that automatic design procedures can be used to obtain more cost efficient designs, and thus reduce the levelized cost of energy from offshore wind. A struct......This thesis presents models and applications for structural optimization of jacket structures for offshore wind turbines. The motivation is that automatic design procedures can be used to obtain more cost efficient designs, and thus reduce the levelized cost of energy from offshore wind....... A structural finite element model is developed specifically for the analysis and optimization of jacket structures. The model uses Timoshenko beam elements, and assumes thin walled tubular beams and a linear elastic structural response. The finite element model is implemented in a Matlab package called JADOP...... (Jacket Design Optimization), and the static and dynamic structural response is verified with the commercial finite element software Abaqus. A parametric mesh of the offshore wind turbine structure makes it relatively easy to represent various structures from the literature, as well as exploring...

Multi-objective three stage design optimization for island microgrids

International Nuclear Information System (INIS)

Sachs, Julia; Sawodny, Oliver

2016-01-01

Highlights: • An enhanced multi-objective three stage design optimization for microgrids is given. • Use of an optimal control problem for the calculation of the optimal operation. • The inclusion of a detailed battery model with CC/CV charging control. • The determination of a representative profile with optimized number of days. • The proposed method finds its direct application in a design tool for microgids. - Abstract: Hybrid off-grid energy systems enable a cost efficient and reliable energy supply to rural areas around the world. The main potential for a low cost operation and uninterrupted power supply lies in the optimal sizing and operation of such microgrids. In particular, sudden variations in load demand or in the power supply from renewables underline the need for an optimally sized system. This paper presents an efficient multi-objective model based optimization approach for the optimal sizing of all components and the determination of the best power electronic layout. The presented method is divided into three optimization problems to minimize economic and environmental objectives. This design optimization includes detailed components models and an optimized energy dispatch strategy which enables the optimal design of the energy system with respect to an adequate control for the specific configuration. To significantly reduce the computation time without loss of accuracy, the presented method contains the determination of a representative load profile using a k-means clustering method. The k-means algorithm itself is embedded in an optimization problem for the calculation of the optimal number of clusters. The benefits in term of reduced computation time, inclusion of optimal energy dispatch and optimization of power electronic architecture, of the presented optimization method are illustrated using a case study.

Numerical optimization of Combined Heat and Power Organic Rankine Cycles – Part A: Design optimization

International Nuclear Information System (INIS)

Martelli, Emanuele; Capra, Federico; Consonni, Stefano

2015-01-01

This two-part paper proposes an approach based on state-of-the-art numerical optimization methods for simultaneously determining the most profitable design and part-load operation of Combined Heat and Power Organic Rankine Cycles. Compared to the usual design practice, the important advantages of the proposed approach are (i) to consider the part-load performance of the ORC at the design stage, (ii) to optimize not only the cycle variables, but also the main turbine design variables (number of stages, stage loads, rotational speed). In this first part (Part A), the design model and the optimization algorithm are presented and tested on a real-world test case. PGS-COM, a recently proposed hybrid derivative-free algorithm, allows to efficiently tackle the challenging non-smooth black-box problem. - Highlights: • Algorithm for the simultaneous optimization Organic Rakine Cycle and turbine. • Thermodynamic and economic models of boiler, cycle, turbine are developed. • Non-smooth black-box optimization problem is successfully tackled with PGS-COM. • Test cases show that the algorithm returns optimal solutions within 4 min. • Toluene outperforms MDM (a siloxane) in terms of efficiency and costs.

Design Buildings Optimally: A Lifecycle Assessment Approach

KAUST Repository

Hosny, Ossama

2013-01-01

This paper structures a generic framework to support optimum design for multi-buildings in desert environment. The framework is targeting an environmental friendly design with minimum lifecycle cost, using Genetic Algorithms (Gas). GAs function through a set of success measures which evaluates the design, formulates a proper objective, and reflects possible tangible/intangible constraints. The framework optimizes the design and categorizes it under a certain environmental category at minimum Life Cycle Cost (LCC). It consists of three main modules: (1) a custom Building InformationModel (BIM) for desert buildings with a compatibility checker as a central interactive database; (2) a system evaluator module to evaluate the proposed success measures for the design; and (3) a GAs optimization module to ensure optimum design. The framework functions through three levels: the building components, integrated building, and multi-building levels. At the component level the design team should be able to select components in a designed sequence to ensure compatibility among various components, while at the building level; the team can relatively locate and orient each individual building. Finally, at the multi-building (compound) level the whole design can be evaluated using success measures of natural light, site capacity, shading impact on natural lighting, thermal change, visual access and energy saving. The framework through genetic algorithms optimizes the design by determining proper types of building components and relative buildings locations and orientations which ensure categorizing the design under a specific category or meet certain preferences at minimum lifecycle cost.

Optimal Design of Modern Transformerless PV Inverter Topologies

OpenAIRE

Saridakis, Stefanos; Koutroulis, Eftichios; Blaabjerg, Frede

2013-01-01

The design optimization of H5, H6, neutral point clamped, active-neutral point clamped, and conergy-NPC transformerless photovoltaic (PV) inverters is presented in this paper. The components reliability in terms of the corresponding malfunctions, affecting the PV inverter maintenance cost during the operational lifetime period of the PV installation, is also considered in the optimization process. According to the results of the proposed design method, different optimal values of the PV inver...

A procedure for multi-objective optimization of tire design parameters

OpenAIRE

Nikola Korunović; Miloš Madić; Miroslav Trajanović; Miroslav Radovanović

2015-01-01

The identification of optimal tire design parameters for satisfying different requirements, i.e. tire performance characteristics, plays an essential role in tire design. In order to improve tire performance characteristics, formulation and solving of multi-objective optimization problem must be performed. This paper presents a multi-objective optimization procedure for determination of optimal tire design parameters for simultaneous minimization of strain energy density at two distinctive zo...

Software for CATV Design and Frequency Plan Optimization

Directory of Open Access Journals (Sweden)

O. Hala

2007-09-01

Full Text Available The paper deals with the structure of a software medium used for design and sub-optimization of frequency plan in CATV networks, their description and design method. The software performance is described and a simple design example of energy balance of a simplified CATV network is given. The software was created in programming environment called Delphi and local optimization was made in Matlab.

The optimization of treatment and management of schizophrenia in Europe (OPTiMiSE) trial

DEFF Research Database (Denmark)

Leucht, Stefan; Winter-van Rossum, Inge; Heres, Stephan

2015-01-01

Commission sponsored "Optimization of Treatment and Management of Schizophrenia in Europe" (OPTiMiSE) trial which aims to provide a treatment algorithm for patients with a first episode of schizophrenia. METHODS: We searched Pubmed (October 29, 2014) for randomized controlled trials (RCTs) that examined...... switching the drug in nonresponders to another antipsychotic. We described important methodological choices of the OPTiMiSE trial. RESULTS: We found 10 RCTs on switching antipsychotic drugs. No trial was conclusive and none was concerned with first-episode schizophrenia. In OPTiMiSE, 500 first episode...

Multiobjective hyper heuristic scheme for system design and optimization

Science.gov (United States)

Rafique, Amer Farhan

2012-11-01

As system design is becoming more and more multifaceted, integrated, and complex, the traditional single objective optimization trends of optimal design are becoming less and less efficient and effective. Single objective optimization methods present a unique optimal solution whereas multiobjective methods present pareto front. The foremost intent is to predict a reasonable distributed pareto-optimal solution set independent of the problem instance through multiobjective scheme. Other objective of application of intended approach is to improve the worthiness of outputs of the complex engineering system design process at the conceptual design phase. The process is automated in order to provide the system designer with the leverage of the possibility of studying and analyzing a large multiple of possible solutions in a short time. This article presents Multiobjective Hyper Heuristic Optimization Scheme based on low level meta-heuristics developed for the application in engineering system design. Herein, we present a stochastic function to manage meta-heuristics (low-level) to augment surety of global optimum solution. Generic Algorithm, Simulated Annealing and Swarm Intelligence are used as low-level meta-heuristics in this study. Performance of the proposed scheme is investigated through a comprehensive empirical analysis yielding acceptable results. One of the primary motives for performing multiobjective optimization is that the current engineering systems require simultaneous optimization of conflicting and multiple. Random decision making makes the implementation of this scheme attractive and easy. Injecting feasible solutions significantly alters the search direction and also adds diversity of population resulting in accomplishment of pre-defined goals set in the proposed scheme.

Design of the Endobronchial Valve for Emphysema Palliation Trial (VENT: a non-surgical method of lung volume reduction

Directory of Open Access Journals (Sweden)

Noppen Marc

2007-07-01

Full Text Available Abstract Background Lung volume reduction surgery is effective at improving lung function, quality of life, and mortality in carefully selected individuals with advanced emphysema. Recently, less invasive bronchoscopic approaches have been designed to utilize these principles while avoiding the associated perioperative risks. The Endobronchial Valve for Emphysema PalliatioN Trial (VENT posits that occlusion of a single pulmonary lobe through bronchoscopically placed Zephyr® endobronchial valves will effect significant improvements in lung function and exercise tolerance with an acceptable risk profile in advanced emphysema. Methods The trial design posted on Clinical trials.gov, on August 10, 2005 proposed an enrollment of 270 subjects. Inclusion criteria included: diagnosis of emphysema with forced expiratory volume in one second (FEV1 100%; residual volume > 150% predicted, and heterogeneous emphysema defined using a quantitative chest computed tomography algorithm. Following standardized pulmonary rehabilitation, patients were randomized 2:1 to receive unilateral lobar placement of endobronchial valves plus optimal medical management or optimal medical management alone. The co-primary endpoint was the mean percent change in FEV1 and six minute walk distance at 180 days. Secondary end-points included mean percent change in St. George's Respiratory Questionnaire score and the mean absolute changes in the maximal work load measured by cycle ergometry, dyspnea (mMRC score, and total oxygen use per day. Per patient response rates in clinically significant improvement/maintenance of FEV1 and six minute walk distance and technical success rates of valve placement were recorded. Apriori response predictors based on quantitative CT and lung physiology were defined. Conclusion If endobronchial valves improve FEV1 and health status with an acceptable safety profile in advanced emphysema, they would offer a novel intervention for this progressive and

Optimal Design of Gradient Materials and Bi-Level Optimization of Topology Using Targets (BOTT)

Science.gov (United States)

Garland, Anthony

The objective of this research is to understand the fundamental relationships necessary to develop a method to optimize both the topology and the internal gradient material distribution of a single object while meeting constraints and conflicting objectives. Functionally gradient material (FGM) objects possess continuous varying material properties throughout the object, and they allow an engineer to tailor individual regions of an object to have specific mechanical properties by locally modifying the internal material composition. A variety of techniques exists for topology optimization, and several methods exist for FGM optimization, but combining the two together is difficult. Understanding the relationship between topology and material gradient optimization enables the selection of an appropriate model and the development of algorithms, which allow engineers to design high-performance parts that better meet design objectives than optimized homogeneous material objects. For this research effort, topology optimization means finding the optimal connected structure with an optimal shape. FGM optimization means finding the optimal macroscopic material properties within an object. Tailoring the material constitutive matrix as a function of position results in gradient properties. Once, the target macroscopic properties are known, a mesostructure or a particular material nanostructure can be found which gives the target material properties at each macroscopic point. This research demonstrates that topology and gradient materials can both be optimized together for a single part. The algorithms use a discretized model of the domain and gradient based optimization algorithms. In addition, when considering two conflicting objectives the algorithms in this research generate clear 'features' within a single part. This tailoring of material properties within different areas of a single part (automated design of 'features') using computational design tools is a novel benefit

Methodology for designing aircraft having optimal sound signatures

NARCIS (Netherlands)

Sahai, A.K.; Simons, D.G.

2017-01-01

This paper presents a methodology with which aircraft designs can be modified such that they produce optimal sound signatures on the ground. With optimal sound it is implied in this case sounds that are perceived as less annoying by residents living near airport vicinities. A novel design and

High-efficiency design optimization of a centrifugal pump

Energy Technology Data Exchange (ETDEWEB)

Heo, Man Woong; Ma, Sang Bum; Shim, Hyeon Seok; Kim, Kwang Yong [Dept. of Mechanical Engineering, Inha University, Incheon (Korea, Republic of)

2016-09-15

Design optimization of a backward-curved blades centrifugal pump with specific speed of 150 has been performed to improve hydraulic performance of the pump using surrogate modeling and three-dimensional steady Reynolds-averaged Navier-Stokes analysis. The shear stress transport model was used for the analysis of turbulence. Four geometric variables defining the blade hub inlet angle, hub contours, blade outlet angle, and blade angle profile of impeller were selected as design variables, and total efficiency of the pump at design flow rate was set as the objective function for the optimization. Thirty-six design points were chosen using the Latin hypercube sampling, and three different surrogate models were constructed using the objective function values calculated at these design points. The optimal point was searched from the constructed surrogate model by using sequential quadratic programming. The optimum designs of the centrifugal pump predicted by the surrogate models show considerable increases in efficiency compared to a reference design. Performance of the best optimum design was validated compared to experimental data for total efficiency and head.

Determining the Optimal Protocol for Measuring an Albuminuria Class Transition in Clinical Trials in Diabetic Kidney Disease

DEFF Research Database (Denmark)

Kröpelin, Tobias F; de Zeeuw, Dick; Remuzzi, Giuseppe

2016-01-01

Albuminuria class transition (normo- to micro- to macroalbuminuria) is used as an intermediate end point to assess renoprotective drug efficacy. However, definitions of such class transition vary between trials. To determine the most optimal protocol, we evaluated the approaches used in four...... effect increased (decreased precision) with stricter end point definitions, resulting in a loss of statistical significance. In conclusion, the optimal albuminuria transition end point for use in drug intervention trials can be determined with a single urine collection for albuminuria assessment per...... clinical trials testing the effect of renin-angiotensin-aldosterone system intervention on albuminuria class transition in patients with diabetes: the BENEDICT, the DIRECT, the ALTITUDE, and the IRMA-2 Trial. The definition of albuminuria class transition used in each trial differed from the definitions...

Community-led trials: Intervention co-design in a cluster randomised controlled trial.

Science.gov (United States)

Andersson, Neil

2017-05-30

In conventional randomised controlled trials (RCTs), researchers design the interventions. In the Camino Verde trial, each intervention community designed its own programmes to prevent dengue. Instead of fixed actions or menus of activities to choose from, the trial randomised clusters to a participatory research protocol that began with sharing and discussing evidence from a local survey, going on to local authorship of the action plan for vector control.Adding equitable stakeholder engagement to RCT infrastructure anchors the research culturally, making it more meaningful to stakeholders. Replicability in other conditions is straightforward, since all intervention clusters used the same engagement protocol to discuss and to mobilize for dengue prevention. The ethical codes associated with RCTs play out differently in community-led pragmatic trials, where communities essentially choose what they want to do. Several discussion groups in each intervention community produced multiple plans for prevention, recognising different time lines. Some chose fast turnarounds, like elimination of breeding sites, and some chose longer term actions like garbage disposal and improving water supplies.A big part of the skill set for community-led trials is being able to stand back and simply support communities in what they want to do and how they want to do it, something that does not come naturally to many vector control programs or to RCT researchers. Unexpected negative outcomes can come from the turbulence implicit in participatory research. One example was the gender dynamic in the Mexican arm of the Camino Verde trial. Strong involvement of women in dengue control activities seems to have discouraged men in settings where activity in public spaces or outside of the home would ordinarily be considered a "male competence".Community-led trials address the tension between one-size-fits-all programme interventions and local needs. Whatever the conventional wisdom about how

Community-led trials: Intervention co-design in a cluster randomised controlled trial

Directory of Open Access Journals (Sweden)

Neil Andersson

2017-05-01

Full Text Available Abstract In conventional randomised controlled trials (RCTs, researchers design the interventions. In the Camino Verde trial, each intervention community designed its own programmes to prevent dengue. Instead of fixed actions or menus of activities to choose from, the trial randomised clusters to a participatory research protocol that began with sharing and discussing evidence from a local survey, going on to local authorship of the action plan for vector control. Adding equitable stakeholder engagement to RCT infrastructure anchors the research culturally, making it more meaningful to stakeholders. Replicability in other conditions is straightforward, since all intervention clusters used the same engagement protocol to discuss and to mobilize for dengue prevention. The ethical codes associated with RCTs play out differently in community-led pragmatic trials, where communities essentially choose what they want to do. Several discussion groups in each intervention community produced multiple plans for prevention, recognising different time lines. Some chose fast turnarounds, like elimination of breeding sites, and some chose longer term actions like garbage disposal and improving water supplies. A big part of the skill set for community-led trials is being able to stand back and simply support communities in what they want to do and how they want to do it, something that does not come naturally to many vector control programs or to RCT researchers. Unexpected negative outcomes can come from the turbulence implicit in participatory research. One example was the gender dynamic in the Mexican arm of the Camino Verde trial. Strong involvement of women in dengue control activities seems to have discouraged men in settings where activity in public spaces or outside of the home would ordinarily be considered a “male competence”. Community-led trials address the tension between one-size-fits-all programme interventions and local needs. Whatever the

Robust Design Optimization of an Aerospace Vehicle Prolusion System

Directory of Open Access Journals (Sweden)

Muhammad Aamir Raza

2011-01-01

Full Text Available This paper proposes a robust design optimization methodology under design uncertainties of an aerospace vehicle propulsion system. The approach consists of 3D geometric design coupled with complex internal ballistics, hybrid optimization, worst-case deviation, and efficient statistical approach. The uncertainties are propagated through worst-case deviation using first-order orthogonal design matrices. The robustness assessment is measured using the framework of mean-variance and percentile difference approach. A parametric sensitivity analysis is carried out to analyze the effects of design variables variation on performance parameters. A hybrid simulated annealing and pattern search approach is used as an optimizer. The results show the objective function of optimizing the mean performance and minimizing the variation of performance parameters in terms of thrust ratio and total impulse could be achieved while adhering to the system constraints.

More ethical and more efficient clinical research: multiplex trial design.

Science.gov (United States)

Keus, Frederik; van der Horst, Iwan C C; Nijsten, Maarten W

2014-08-14

Today's clinical research faces challenges such as a lack of clinical equipoise between treatment arms, reluctance in randomizing for multiple treatments simultaneously, inability to address interactions and increasingly restricted resources. Furthermore, many trials are biased by extensive exclusion criteria, relatively small sample size and less appropriate outcome measures. We propose a 'Multiplex' trial design that preserves clinical equipoise with a continuous and factorial trial design that will also result in more efficient use of resources. This multiplex design accommodates subtrials with appropriate choice of treatment arms within each subtrial. Clinical equipoise should increase consent rates while the factorial design is the best way to identify interactions. The multiplex design may evolve naturally from today's research limitations and challenges, while principal objections seem absent. However this new design poses important infrastructural, organisational and psychological challenges that need in depth consideration.

Optimal cure cycle design of a resin-fiber composite laminate

Science.gov (United States)

Hou, Jean W.; Sheen, Jeenson

1987-01-01

A unified computed aided design method was studied for the cure cycle design that incorporates an optimal design technique with the analytical model of a composite cure process. The preliminary results of using this proposed method for optimal cure cycle design are reported and discussed. The cure process of interest is the compression molding of a polyester which is described by a diffusion reaction system. The finite element method is employed to convert the initial boundary value problem into a set of first order differential equations which are solved simultaneously by the DE program. The equations for thermal design sensitivities are derived by using the direct differentiation method and are solved by the DE program. A recursive quadratic programming algorithm with an active set strategy called a linearization method is used to optimally design the cure cycle, subjected to the given design performance requirements. The difficulty of casting the cure cycle design process into a proper mathematical form is recognized. Various optimal design problems are formulated to address theses aspects. The optimal solutions of these formulations are compared and discussed.

Towards robust optimal design of storm water systems

Science.gov (United States)

Marquez Calvo, Oscar; Solomatine, Dimitri

2015-04-01

In this study the focus is on the design of a storm water or a combined sewer system. Such a system should be capable to handle properly most of the storm to minimize the damages caused by flooding due to the lack of capacity of the system to cope with rain water at peak times. This problem is a multi-objective optimization problem: we have to take into account the minimization of the construction costs, the minimization of damage costs due to flooding, and possibly other criteria. One of the most important factors influencing the design of storm water systems is the expected amount of water to deal with. It is common that this infrastructure is developed with the capacity to cope with events that occur once in, say 10 or 20 years - so-called design rainfall events. However, rainfall is a random variable and such uncertainty typically is not taken explicitly into account in optimization. Rainfall design data is based on historical information of rainfalls, but many times this data is based on unreliable measures; or in not enough historical information; or as we know, the patterns of rainfall are changing regardless of historical information. There are also other sources of uncertainty influencing design, for example, leakages in the pipes and accumulation of sediments in pipes. In the context of storm water or combined sewer systems design or rehabilitation, robust optimization technique should be able to find the best design (or rehabilitation plan) within the available budget but taking into account uncertainty in those variables that were used to design the system. In this work we consider various approaches to robust optimization proposed by various authors (Gabrel, Murat, Thiele 2013; Beyer, Sendhoff 2007) and test a novel method ROPAR (Solomatine 2012) to analyze robustness. References Beyer, H.G., & Sendhoff, B. (2007). Robust optimization - A comprehensive survey. Comput. Methods Appl. Mech. Engrg., 3190-3218. Gabrel, V.; Murat, C., Thiele, A. (2014

Fusion blanket design and optimization techniques

International Nuclear Information System (INIS)

Gohar, Y.

2005-01-01

In fusion reactors, the blanket design and its characteristics have a major impact on the reactor performance, size, and economics. The selection and arrangement of the blanket materials, dimensions of the different blanket zones, and different requirements of the selected materials for a satisfactory performance are the main parameters, which define the blanket performance. These parameters translate to a large number of variables and design constraints, which need to be simultaneously considered in the blanket design process. This represents a major design challenge because of the lack of a comprehensive design tool capable of considering all these variables to define the optimum blanket design and satisfying all the design constraints for the adopted figure of merit and the blanket design criteria. The blanket design techniques of the First Wall/Blanket/Shield Design and Optimization System (BSDOS) have been developed to overcome this difficulty and to provide the state-of-the-art techniques and tools for performing blanket design and analysis. This report describes some of the BSDOS techniques and demonstrates its use. In addition, the use of the optimization technique of the BSDOS can result in a significant blanket performance enhancement and cost saving for the reactor design under consideration. In this report, examples are presented, which utilize an earlier version of the ITER solid breeder blanket design and a high power density self-cooled lithium blanket design for demonstrating some of the BSDOS blanket design techniques

Model-based Organization Manning, Strategy, and Structure Design via Team Optimal Design (TOD) Methodology

National Research Council Canada - National Science Library

Levchuk, Georgiy; Chopra, Kari; Paley, Michael; Levchuk, Yuri; Clark, David

2005-01-01

This paper describes a quantitative Team Optimal Design (TOD) methodology and its application to the design of optimized manning for E-10 Multi-sensor Command and Control Aircraft. The E-10 (USAF, 2002...

Optimal Design of Laminated Composite Beams

DEFF Research Database (Denmark)

Blasques, José Pedro Albergaria Amaral

model for the analysis of laminated composite beams is proposed. The structural analysis is performed in a beam finite element context. The development of a finite element based tool for the analysis of the cross section stiffness properties is described. The resulting beam finite element formulation...... is able to account for the effects of material anisotropy and inhomogeneity in the global response of the beam. Beam finite element models allow for a significant reduction in problem size and are therefore an efficient alternative in computationally intensive applications like optimization frameworks...... design of laminated composite beams. The devised framework is applied in the optimal design of laminated composite beams with different cross section geometries and subjected to different load cases. Design criteria such as beam stiffness, weight, magnitude of the natural frequencies of vibration...

The OPTIMIZE trial: Rationale and design of a randomized controlled trial of motivational enhancement therapy to improve adherence to statin medication.

Science.gov (United States)

Rash, Joshua A; Lavoie, Kim L; Sigal, Ronald J; Campbell, David J T; Manns, Braden J; Tonelli, Marcello; Campbell, Tavis S

2016-07-01

Statins are a class of medications that are particularly effective for lowering cholesterol and reducing cardiovascular morbidity and mortality. Despite a range of benefits, non-adherence to statin medication is prevalent with 50% to 75% of patients failing to adhere to treatment within the first 2-years. A previous review on interventions to improve adherence to cholesterol lowering medication concluded that rigorous trials were needed with emphasis on the patient's perspective and shared decision making. Motivational interviewing (MInt) is a promising patient-centered approach for improving adherence in patients with chronic diseases. This manuscript describes the rational and design of a randomized controlled trial (RCT) testing the efficacy of MInt in improving adherence to statin medication. Patients filling their first statin prescription will be recruited to complete a 6-month observation run-in period (phase-1) after which medication possession ratio (MPR) will be assessed. Patients meeting criteria for non-adherence (MPR≤60%) will be invited to participate in the trial. 336 non-adherent new statin users will undergo a fasting lipid panel, complete baseline questionnaires, and be randomly allocated to receive four sessions of adherence education delivered using MInt (EdMInt) or to an education control (EC) delivered at 3-month intervals. Final assessments will occur 12-months after the first EdMInt or EC session. The primary outcome is change in MPR adherence to statin medication from baseline to 12-months. Secondary outcomes include within-patient change in self-reported medication adherence, stage of change and self-efficacy for medication adherence, motivation to adhere to statin medication, and lipid profile. Copyright © 2016 Elsevier Inc. All rights reserved.

On the design of compliant mechanisms using topology optimization

DEFF Research Database (Denmark)

Sigmund, Ole

1997-01-01

This paper presents a method for optimal design of compliant mechanism topologies. The method is based on continuum-type topology optimization techniques and finds the optimal compliant mechanism topology within a given design domain and a given position and direction of input and output forces....... By constraining the allowed displacement at the input port, it is possible to control the maximum stress level in the compliant mechanism. The ability of the design method to find a mechanism with complex output behavior is demonstrated by several examples. Some of the optimal mechanism topologies have been...... manufactured, both in macroscale (hand-size) made in Nylon, and in microscale (

Surrogate Assisted Design Optimization of an Air Turbine

Directory of Open Access Journals (Sweden)

Rameez Badhurshah

2014-01-01

Full Text Available Surrogates are cheaper to evaluate and assist in designing systems with lesser time. On the other hand, the surrogates are problem dependent and they need evaluation for each problem to find a suitable surrogate. The Kriging variants such as ordinary, universal, and blind along with commonly used response surface approximation (RSA model were used in the present problem, to optimize the performance of an air impulse turbine used for ocean wave energy harvesting by CFD analysis. A three-level full factorial design was employed to find sample points in the design space for two design variables. A Reynolds-averaged Navier Stokes solver was used to evaluate the objective function responses, and these responses along with the design variables were used to construct the Kriging variants and RSA functions. A hybrid genetic algorithm was used to find the optimal point in the design space. It was found that the best optimal design was produced by the universal Kriging while the blind Kriging produced the worst. The present approach is suggested for renewable energy application.

Design optimization for cost and quality: The robust design approach

Science.gov (United States)

Unal, Resit

1990-01-01

Designing reliable, low cost, and operable space systems has become the key to future space operations. Designing high quality space systems at low cost is an economic and technological challenge to the designer. A systematic and efficient way to meet this challenge is a new method of design optimization for performance, quality, and cost, called Robust Design. Robust Design is an approach for design optimization. It consists of: making system performance insensitive to material and subsystem variation, thus allowing the use of less costly materials and components; making designs less sensitive to the variations in the operating environment, thus improving reliability and reducing operating costs; and using a new structured development process so that engineering time is used most productively. The objective in Robust Design is to select the best combination of controllable design parameters so that the system is most robust to uncontrollable noise factors. The robust design methodology uses a mathematical tool called an orthogonal array, from design of experiments theory, to study a large number of decision variables with a significantly small number of experiments. Robust design also uses a statistical measure of performance, called a signal-to-noise ratio, from electrical control theory, to evaluate the level of performance and the effect of noise factors. The purpose is to investigate the Robust Design methodology for improving quality and cost, demonstrate its application by the use of an example, and suggest its use as an integral part of space system design process.

Optimization of straight-sided spline design

DEFF Research Database (Denmark)

Pedersen, Niels Leergaard

2011-01-01

and the subject of improving the design. The present paper concentrates on the optimization of splines and the predictions of stress concentrations, which are determined by finite element analysis (FEA). Using different design modifications, that do not change the spline load carrying capacity, it is shown...

A Bayesian Optimal Design for Sequential Accelerated Degradation Testing

Directory of Open Access Journals (Sweden)

Xiaoyang Li

2017-07-01

Full Text Available When optimizing an accelerated degradation testing (ADT plan, the initial values of unknown model parameters must be pre-specified. However, it is usually difficult to obtain the exact values, since many uncertainties are embedded in these parameters. Bayesian ADT optimal design was presented to address this problem by using prior distributions to capture these uncertainties. Nevertheless, when the difference between a prior distribution and actual situation is large, the existing Bayesian optimal design might cause some over-testing or under-testing issues. For example, the implemented ADT following the optimal ADT plan consumes too much testing resources or few accelerated degradation data are obtained during the ADT. To overcome these obstacles, a Bayesian sequential step-down-stress ADT design is proposed in this article. During the sequential ADT, the test under the highest stress level is firstly conducted based on the initial prior information to quickly generate degradation data. Then, the data collected under higher stress levels are employed to construct the prior distributions for the test design under lower stress levels by using the Bayesian inference. In the process of optimization, the inverse Gaussian (IG process is assumed to describe the degradation paths, and the Bayesian D-optimality is selected as the optimal objective. A case study on an electrical connector’s ADT plan is provided to illustrate the application of the proposed Bayesian sequential ADT design method. Compared with the results from a typical static Bayesian ADT plan, the proposed design could guarantee more stable and precise estimations of different reliability measures.

Optimization methods in structural design

CERN Document Server

Rothwell, Alan

2017-01-01

This book offers an introduction to numerical optimization methods in structural design. Employing a readily accessible and compact format, the book presents an overview of optimization methods, and equips readers to properly set up optimization problems and interpret the results. A ‘how-to-do-it’ approach is followed throughout, with less emphasis at this stage on mathematical derivations. The book features spreadsheet programs provided in Microsoft Excel, which allow readers to experience optimization ‘hands-on.’ Examples covered include truss structures, columns, beams, reinforced shell structures, stiffened panels and composite laminates. For the last three, a review of relevant analysis methods is included. Exercises, with solutions where appropriate, are also included with each chapter. The book offers a valuable resource for engineering students at the upper undergraduate and postgraduate level, as well as others in the industry and elsewhere who are new to these highly practical techniques.Whi...

NDDP multi-stage flash desalination process simulator design process optimization

International Nuclear Information System (INIS)

Sashi Kumar, G.N.; Mahendra, A.K.; Sanyal, A.; Gouthaman, G.

2009-03-01

The improvement of NDDP-MSF plant's performance ratio (PR) from design value of 9.0 to 13.1 was achieved by optimizing the plant's operating parameters within the feasible zone of operation. This plant has 20% excess heat transfer area over the design condition which helped us to get a PR of 15.1 after optimization. Thus we have obtained, (1) A 45% increase in the output over design value by the optimization carried out with design heat transfer area. (2) A 68% increase in the output over design value by the optimization carried out with increased heat transfer area. This report discusses the approach, methodology and results of the optimization study carried out. A simulator, MSFSIM which predicts the performance of a multi-stage flash (MSF) desalination plant has been coupled with Genetic Algorithm (GA) optimizer. Exhaustive optimization case studies have been conducted on this plant with an objective to increase the performance ratio (PR). The steady state optimization performed was based on obtaining the best stage wise pressure profile to enhance thermal efficiency which in-turn improves the performance ratio. Apart from this, the recirculating brine flow rate was also optimized. This optimization study enabled us to increase the PR of NDDP-MSF plant from design value of 9.0 to an optimized value 13.1. The actual plant is provided with 20% additional heat transfer area over and above the design heat transfer area. Optimization with this additional heat transfer area has taken the PR to 15.1. A desire to maintain equal flashing rates in all of the stages (a feature required for long life of the plant and to avoid cascading effect of non-flashing triggered by any stage) of the MSF plant has also been achieved. The deviation in the flashing rates within stages has been reduced. The startup characteristic of the plant (i.e the variation of stage pressure and the variation of recirculation flow rate with time), have been optimized with a target to minimize the

Automated magnetic divertor design for optimal power exhaust

Energy Technology Data Exchange (ETDEWEB)

Blommaert, Maarten

2017-07-01

The so-called divertor is the standard particle and power exhaust system of nuclear fusion tokamaks. In essence, the magnetic configuration hereby 'diverts' the plasma to a specific divertor structure. The design of this divertor is still a key issue to be resolved to evolve from experimental fusion tokamaks to commercial power plants. The focus of this dissertation is on one particular design requirement: avoiding excessive heat loads on the divertor structure. The divertor design process is assisted by plasma edge transport codes that simulate the plasma and neutral particle transport in the edge of the reactor. These codes are computationally extremely demanding, not in the least due to the complex collisional processes between plasma and neutrals that lead to strong radiation sinks and macroscopic heat convection near the vessel walls. One way of improving the heat exhaust is by modifying the magnetic confinement that governs the plasma flow. In this dissertation, automated design of the magnetic configuration is pursued using adjoint based optimization methods. A simple and fast perturbation model is used to compute the magnetic field in the vacuum vessel. A stable optimal design method of the nested type is then elaborated that strictly accounts for several nonlinear design constraints and code limitations. Using appropriate cost function definitions, the heat is spread more uniformly over the high-heat load plasma-facing components in a practical design example. Furthermore, practical in-parts adjoint sensitivity calculations are presented that provide a way to an efficient optimization procedure. Results are elaborated for a fictituous JET (Joint European Torus) case. The heat load is strongly reduced by exploiting an expansion of the magnetic flux towards the solid divertor structure. Subsequently, shortcomings of the perturbation model for magnetic field calculations are discussed in comparison to a free boundary equilibrium (FBE) simulation

Automated magnetic divertor design for optimal power exhaust

International Nuclear Information System (INIS)

Blommaert, Maarten

2017-01-01

The so-called divertor is the standard particle and power exhaust system of nuclear fusion tokamaks. In essence, the magnetic configuration hereby 'diverts' the plasma to a specific divertor structure. The design of this divertor is still a key issue to be resolved to evolve from experimental fusion tokamaks to commercial power plants. The focus of this dissertation is on one particular design requirement: avoiding excessive heat loads on the divertor structure. The divertor design process is assisted by plasma edge transport codes that simulate the plasma and neutral particle transport in the edge of the reactor. These codes are computationally extremely demanding, not in the least due to the complex collisional processes between plasma and neutrals that lead to strong radiation sinks and macroscopic heat convection near the vessel walls. One way of improving the heat exhaust is by modifying the magnetic confinement that governs the plasma flow. In this dissertation, automated design of the magnetic configuration is pursued using adjoint based optimization methods. A simple and fast perturbation model is used to compute the magnetic field in the vacuum vessel. A stable optimal design method of the nested type is then elaborated that strictly accounts for several nonlinear design constraints and code limitations. Using appropriate cost function definitions, the heat is spread more uniformly over the high-heat load plasma-facing components in a practical design example. Furthermore, practical in-parts adjoint sensitivity calculations are presented that provide a way to an efficient optimization procedure. Results are elaborated for a fictituous JET (Joint European Torus) case. The heat load is strongly reduced by exploiting an expansion of the magnetic flux towards the solid divertor structure. Subsequently, shortcomings of the perturbation model for magnetic field calculations are discussed in comparison to a free boundary equilibrium (FBE) simulation. These flaws

SINGLE VERSUS MULTIPLE TRIAL VECTORS IN CLASSICAL DIFFERENTIAL EVOLUTION FOR OPTIMIZING THE QUANTIZATION TABLE IN JPEG BASELINE ALGORITHM

Directory of Open Access Journals (Sweden)

B Vinoth Kumar

2017-07-01

Full Text Available Quantization Table is responsible for compression / quality trade-off in baseline Joint Photographic Experts Group (JPEG algorithm and therefore it is viewed as an optimization problem. In the literature, it has been found that Classical Differential Evolution (CDE is a promising algorithm to generate the optimal quantization table. However, the searching capability of CDE could be limited due to generation of single trial vector in an iteration which in turn reduces the convergence speed. This paper studies the performance of CDE by employing multiple trial vectors in a single iteration. An extensive performance analysis has been made between CDE and CDE with multiple trial vectors in terms of Optimization process, accuracy, convergence speed and reliability. The analysis report reveals that CDE with multiple trial vectors improves the convergence speed of CDE and the same is confirmed using a statistical hypothesis test (t-test.

Refining design of superconducting magnets synchronous with winding using particle swarm optimization

International Nuclear Information System (INIS)

Du, J.J.; Wu, W.; Mei, E.M.; Yuan, P.; Ma, L.Z.; Dong, Z.W.

2013-01-01

Highlights: ► A method of synchronous optimization design of superconducting magnets is proposed. ► We get a refining design of a main magnet on Lanzhou Penning Trap by the method. ► We expounds the necessity of tracking optimizing of coils for magnets. ► Particle swarm optimization shows effectiveness in magnet optimization. ► The expected homogeneity of the magnet improves considerably. -- Abstract: A methodology of synchronous optimization design of magnets under construction according to original design scheme is put forward in this paper, and it has been successfully used for refining design of a superconducting magnet on Lanzhou Penning Trap (LPT). This paper expounds the necessity of tracking optimization of magnet coil in the process of traditional manufacturing, and optimization design of magnet coils by particle swarm optimization is proposed. Particle swarm optimization is turned out to be an effective design method for magnet optimization. The expected homogeneity of the magnet is improved to 200 ppm from 1150 ppm through the refining optimizing, which provides important guarantee for required homogeneity of the whole magnet

On CAD-integrated Structural Topology and Design Optimization

DEFF Research Database (Denmark)

Olhoff, Niels; Bendsøe, M.P.; Rasmussen, John

1991-01-01

Concepts underlying an interactive CAD-based engineering design optimization system are developed, and methods of optimizing the topology, shape and sizing of mechanical components are presented. These methods are integrated in the system, and the method for determining the optimal topology is used...

Application of analytical target cascading method in multidisciplinary design optimization of ship conceptual design

Directory of Open Access Journals (Sweden)

WANG Jian

2017-10-01

Full Text Available [Objectives] Ship conceptual design requires the coordination of many different disciplines for comprehensive optimization, which presents a complicated system design problem affecting several fields of technology. However, the development of overall ship design is relatively slow compared with other subjects. [Methods] The decomposition and coordination strategy of ship design is presented, and the analytical target cascading (ATC method is applied to the multidisciplinary design optimization of the conceptual design phase of ships on this basis. A tank ship example covering the 5 disciplines of buoyancy and stability, rapidity, maneuverability, capacity and economy is established to illustrate the analysis process in the present study. [Results] The results demonstrate the stability, convergence and validity of the ATC method in dealing with the complex coupling effect occurring in ship conceptual design.[Conclusions] The proposed method provides an effective basis for optimization of ship conceptual design.

Strategies for Optimal Design of Structural Systems

DEFF Research Database (Denmark)

Enevoldsen, I.; Sørensen, John Dalsgaard

1992-01-01

Reliability-based design of structural systems is considered. Especially systems where the reliability model is a series system of parallel systems are analysed. A sensitivity analysis for this class of problems is presented. Direct and sequential optimization procedures to solve the optimization...

Hybrid Design Optimization of High Voltage Pulse Transformers for Klystron Modulators

CERN Document Server

Sylvain, Candolfi; Davide, Aguglia; Jerome, Cros

2015-01-01

This paper presents a hybrid optimization methodology for the design of high voltage pulse transformers used in klystron modulators. The optimization process is using simplified 2D FEA design models of the 3D transformer structure. Each intermediate optimal solution is evaluated by 3D FEA and correction coefficients of the 2D FEA models are derived. A new optimization process using 2D FEA models is then performed. The convergence of this hybrid optimal design methodology is obtained with a limited number of time consuming 3D FEA simulations. The method is applied to the optimal design of a monolithic high voltage pulse transformer for the CLIC klystron modulator.

[Orthogonal design method to optimize rehabilitation prescription of pulsed electric field at Jiaji (EX-B 2) points for spinal cord injury].

Science.gov (United States)

Zhang, Lifeng; Zhang, Hui; Wang, Lin; Liu, Yanyan; Sun, Xianyue; Li, Lingyan; Hou, Jing

2015-01-01

By using orthogonal design method to optimnize prescription of pulsed electric field at Jiaji (EX- B 2) points for spinal cord injury (SCI). Fifty six patients of SCI were selected, in which 36 cases were divided into orthogonal design trial and 20 cases were into clinical verification. With 36 patients who received orthogonal design trial, Frankel grading scale was used as observation index to screen optimal prescription of pulsed electric field. Pulse frequency (factor A) included low frequency (factor A(I), 10(2) Hz). moderate frequency (factor A(II), 10(4) Hz) and high frequency (factor A(III), 10(3) Hz); pulse amplitude (factor B) included 0-30 V (factor B ), 0-60 V (factor B(II)) and 0-90 V (factor B(III)); pulse width (factor C) included 0.1 ms (factor C(I)). 0.6 ms (factor C(II)) and 0.9 ms (factor C(III)); acupuncture time (factor D) included one month (DI), three months (D(II)) and five months (D(III)). Twenty patients were used for clinical efficacy observation and the effects of screened optimal pre scription of pulsed electric field at Jiaji (EX-B 2) points combined with regular rehabilitation training on spasm se- verity, score of sensory and motor functions, Barthel index and Frankel score were observed. (1) As results of orthogonal design trial, the optimal prescription was A(III) B(III), C(I), D(III), which were high frequency (10(3) Hz), 0-90 V of pulse amplitude, 0.4 ms of pulse width and 5 months of treatment time. (2) As results of 20 patient clinical verification, Ashworth score, tendon reflex and clonus were all significantly improved (Ppulsed electric field at Jiaji (EX-B 2) points for spinal cord injury is high frequency (10& Hz), 0-90 V of pulse amplitude, 0.4 ms of pulse width and 5 months of treatment time. The optimal prescription of pulsed electric field at Jiaji (EX-B 2) points combined with regular rehabilitation could obviously improve spasm severity, enhance senso- ry and motor functions, and ameliorate activity of daily life and

Design Optimization of Hybrid FRP/RC Bridge

Science.gov (United States)

Papapetrou, Vasileios S.; Tamijani, Ali Y.; Brown, Jeff; Kim, Daewon

2018-04-01

The hybrid bridge consists of a Reinforced Concrete (RC) slab supported by U-shaped Fiber Reinforced Polymer (FRP) girders. Previous studies on similar hybrid bridges constructed in the United States and Europe seem to substantiate these hybrid designs for lightweight, high strength, and durable highway bridge construction. In the current study, computational and optimization analyses were carried out to investigate six composite material systems consisting of E-glass and carbon fibers. Optimization constraints are determined by stress, deflection and manufacturing requirements. Finite Element Analysis (FEA) and optimization software were utilized, and a framework was developed to run the complete analyses in an automated fashion. Prior to that, FEA validation of previous studies on similar U-shaped FRP girders that were constructed in Poland and Texas is presented. A finer optimization analysis is performed for the case of the Texas hybrid bridge. The optimization outcome of the hybrid FRP/RC bridge shows the appropriate composite material selection and cross-section geometry that satisfies all the applicable Limit States (LS) and, at the same time, results in the lightest design. Critical limit states show that shear stress criteria determine the optimum design for bridge spans less than 15.24 m and deflection criteria controls for longer spans. Increased side wall thickness can reduce maximum observed shear stresses, but leads to a high weight penalty. A taller cross-section and a thicker girder base can efficiently lower the observed deflections and normal stresses. Finally, substantial weight savings can be achieved by the optimization framework if base and side-wall thickness are treated as independent variables.

Optimal design of condenser weight

International Nuclear Information System (INIS)

Zheng Jing; Yan Changqi; Wang Jianjun

2011-01-01

The condenser is an important component in nuclear power plants, which dimension and weight will effect the economical performance and the arrangement of the nuclear power plants. In this paper, the calculation model is established according to the design experience. The corresponding codes are also developed, and the sensitivity of design parameters which influence the condenser weight is analyzed. The present design optimization of the condenser, taking the weight minimization as the objective, is carried out with the self-developed complex-genetic algorithm. The results show that the reference condenser design is far from the best scheme, and also verify the feasibility of the complex-genetic algorithm. (authors)

Formulation development and optimization of Lamivudine 300 mg and Tenofovir Disoproxil Fumarate (TDF 300 mg FDC tablets by D-optimal mixture design

Directory of Open Access Journals (Sweden)

Prosper Tibalinda

2016-12-01

Full Text Available The usage of fixed dose combination (FDC tablets of Lamivudine and Tenofovir Disoproxil Fumarate (TDF is increasing due to increased incidences of HIV/Hepatitis B and HIV/TB co-infections. This is likely to increase the financial crisis due to limited resources for funding procurement of ready-made products from the pharmaceuticals manufacturing leading countries. Therefore, production of local oral tablets containing Lamivudine and TDF FDC is inevitable. Lamivudine 300 mg/TDF 300 mg tablets were developed and optimized by D-optimal mixture design and produced by direct compression technique. Twenty trial formulations with independent variables, including PVP-CL 1–12.00%, PVP-K30 1–10.00%, starch-1500 2.5–12.5% and Avicel-PH102 2–19.25% were prepared by direct compression technique. The formulations were assessed on assay, dissolution, friability, weight variation and disintegration time. It was found that assay ranged from 98.13–101.95% for Lamivudine, 98.25–102.84 for TDF, both were within the in-house assay specification of 95 to 105%. Dissolution at single point was above 80% for Lamivudine 93.96–100.55% and 95.85–103.15% for TDF, disintegration time was between 1.92–66.33 min and friability 0.06–12.56%. Out of twenty formulation trials, eight formulations had all parameters in proven acceptable range. On optimization, one formulation with independent variables, PVP-CL 5.67%, PVP-K30 1.00%, Starch-1500 5.76% was selected. The optimized formulation was comparable to the reference product on the market with similarity factor (f2 and difference factor (f1 within the acceptable range for both Lamivudine and TDF.

Integrated design optimization research and development in an industrial environment

Science.gov (United States)

Kumar, V.; German, Marjorie D.; Lee, S.-J.

1989-01-01

An overview is given of a design optimization project that is in progress at the GE Research and Development Center for the past few years. The objective of this project is to develop a methodology and a software system for design automation and optimization of structural/mechanical components and systems. The effort focuses on research and development issues and also on optimization applications that can be related to real-life industrial design problems. The overall technical approach is based on integration of numerical optimization techniques, finite element methods, CAE and software engineering, and artificial intelligence/expert systems (AI/ES) concepts. The role of each of these engineering technologies in the development of a unified design methodology is illustrated. A software system DESIGN-OPT has been developed for both size and shape optimization of structural components subjected to static as well as dynamic loadings. By integrating this software with an automatic mesh generator, a geometric modeler and an attribute specification computer code, a software module SHAPE-OPT has been developed for shape optimization. Details of these software packages together with their applications to some 2- and 3-dimensional design problems are described.

Design optimization of GaAs betavoltaic batteries

International Nuclear Information System (INIS)

Chen Haiyanag; Jiang Lan; Chen Xuyuan

2011-01-01

GaAs junctions are designed and fabricated for betavoltaic batteries. The design is optimized according to the characteristics of GaAs interface states and the diffusion length in the depletion region of GaAs carriers. Under an illumination of 10 mCi cm -2 63 Ni, the open circuit voltage of the optimized batteries is about ∼0.3 V. It is found that the GaAs interface states induce depletion layers on P-type GaAs surfaces. The depletion layer along the P + PN + junction edge isolates the perimeter surface from the bulk junction, which tends to significantly reduce the battery dark current and leads to a high open circuit voltage. The short circuit current density of the optimized junction is about 28 nA cm -2 , which indicates a carrier diffusion length of less than 1 μm. The overall results show that multi-layer P + PN + junctions are the preferred structures for GaAs betavoltaic battery design.

On the design of 1-3 piezo-composites using topology optimization

DEFF Research Database (Denmark)

Sigmund, Ole; Torquato, S.; Aksay, I.A.

1998-01-01

(h)((*))g(h)((*)), and the electromechanical coupling factor k(h)((*)). The piezocomposite consists of piezoelectric rods embedded in an optimal polymer matrix. We use the topology optimization method to design the optimal (porous) matrix microstructure. When we design for maximum d(h)((*)) and d(h)((*))g(h)((*)) the optimal transversally......We use a topology optimization method to design 1-3 piezocomposites with optimal performance characteristics for hydrophone applications. The performance characteristics we focus on are the hydrostatic charge coefficient d(h)((*)), the hydrophone figure of merit d...

Optimal Control Design for a Solar Greenhouse

NARCIS (Netherlands)

Ooteghem, van R.J.C.

2010-01-01

Abstract: An optimal climate control has been designed for a solar greenhouse to achieve optimal crop production with sustainable instead of fossil energy. The solar greenhouse extends a conventional greenhouse with an improved roof cover, ventilation with heat recovery, a heat pump, a heat

Design paper: The CapOpus trial: A randomized, parallel-group, observer-blinded clinical trial of specialized addiction treatment versus treatment as usual for young patients with cannabis abuse and psychosis

Directory of Open Access Journals (Sweden)

Gluud Christian

2008-07-01

Full Text Available Abstract Background A number of studies indicate a link between cannabis-use and psychosis as well as more severe psychosis in those with existing psychotic disorders. There is currently insufficient evidence to decide the optimal way to treat cannabis abuse among patients with psychosis. Objectives The major objective for the CapOpus trial is to evaluate the additional effect on cannabis abuse of a specialized addiction treatment program adding group treatment and motivational interviewing to treatment as usual. Design The trial is designed as a randomized, parallel-group, observer-blinded clinical trial. Patients are primarily recruited through early-psychosis detection teams, community mental health centers, and assertive community treatment teams. Patients are randomized to one of two treatment arms, both lasting six months: 1 specialized addiction treatment plus treatment as usual or 2 treatment as usual. The specialized addiction treatment is manualized and consists of both individual and group-based motivational interviewing and cognitive behavioral therapy, and incorporates both the family and the case manager of the patient. The primary outcome measure will be changes in amount of cannabis consumption over time. Other outcome measures will be psychosis symptoms, cognitive functioning, quality of life, social functioning, and cost-benefit analyses. Trial registration ClinicalTrials.gov NCT00484302.

Simulations for designing and interpreting intervention trials in infectious diseases.

Science.gov (United States)

Halloran, M Elizabeth; Auranen, Kari; Baird, Sarah; Basta, Nicole E; Bellan, Steven E; Brookmeyer, Ron; Cooper, Ben S; DeGruttola, Victor; Hughes, James P; Lessler, Justin; Lofgren, Eric T; Longini, Ira M; Onnela, Jukka-Pekka; Özler, Berk; Seage, George R; Smith, Thomas A; Vespignani, Alessandro; Vynnycky, Emilia; Lipsitch, Marc

2017-12-29

Interventions in infectious diseases can have both direct effects on individuals who receive the intervention as well as indirect effects in the population. In addition, intervention combinations can have complex interactions at the population level, which are often difficult to adequately assess with standard study designs and analytical methods. Herein, we urge the adoption of a new paradigm for the design and interpretation of intervention trials in infectious diseases, particularly with regard to emerging infectious diseases, one that more accurately reflects the dynamics of the transmission process. In an increasingly complex world, simulations can explicitly represent transmission dynamics, which are critical for proper trial design and interpretation. Certain ethical aspects of a trial can also be quantified using simulations. Further, after a trial has been conducted, simulations can be used to explore the possible explanations for the observed effects. Much is to be gained through a multidisciplinary approach that builds collaborations among experts in infectious disease dynamics, epidemiology, statistical science, economics, simulation methods, and the conduct of clinical trials.

Optimal design of robust piezoelectric microgrippers undergoing large displacements

DEFF Research Database (Denmark)

Ruiz, D.; Sigmund, Ole

2018-01-01

Topology optimization combined with optimal design of electrodes is used to design piezoelectric microgrippers. Fabrication at micro-scale presents an important challenge: due to non-symmetrical lamination of the structures, out-of-plane bending spoils the behaviour of the grippers. Suppression...

Design and volume optimization of space structures

KAUST Repository

Jiang, Caigui; Tang, Chengcheng; Seidel, Hans-Peter; Wonka, Peter

2017-01-01

We study the design and optimization of statically sound and materially efficient space structures constructed by connected beams. We propose a systematic computational framework for the design of space structures that incorporates static soundness, approximation of reference surfaces, boundary alignment, and geometric regularity. To tackle this challenging problem, we first jointly optimize node positions and connectivity through a nonlinear continuous optimization algorithm. Next, with fixed nodes and connectivity, we formulate the assignment of beam cross sections as a mixed-integer programming problem with a bilinear objective function and quadratic constraints. We solve this problem with a novel and practical alternating direction method based on linear programming relaxation. The capability and efficiency of the algorithms and the computational framework are validated by a variety of examples and comparisons.

Design and volume optimization of space structures

KAUST Repository

Jiang, Caigui

2017-07-21

We study the design and optimization of statically sound and materially efficient space structures constructed by connected beams. We propose a systematic computational framework for the design of space structures that incorporates static soundness, approximation of reference surfaces, boundary alignment, and geometric regularity. To tackle this challenging problem, we first jointly optimize node positions and connectivity through a nonlinear continuous optimization algorithm. Next, with fixed nodes and connectivity, we formulate the assignment of beam cross sections as a mixed-integer programming problem with a bilinear objective function and quadratic constraints. We solve this problem with a novel and practical alternating direction method based on linear programming relaxation. The capability and efficiency of the algorithms and the computational framework are validated by a variety of examples and comparisons.

Evaluation of Frameworks for HSCT Design Optimization

Science.gov (United States)

Krishnan, Ramki

1998-01-01

This report is an evaluation of engineering frameworks that could be used to augment, supplement, or replace the existing FIDO 3.5 (Framework for Interdisciplinary Design and Optimization Version 3.5) framework. The report begins with the motivation for this effort, followed by a description of an "ideal" multidisciplinary design and optimization (MDO) framework. The discussion then turns to how each candidate framework stacks up against this ideal. This report ends with recommendations as to the "best" frameworks that should be down-selected for detailed review.

Numerical simulation and optimized design of cased telescoped ammunition interior ballistic

Directory of Open Access Journals (Sweden)

Jia-gang Wang

2018-04-01

Full Text Available In order to achieve the optimized design of a cased telescoped ammunition (CTA interior ballistic design, a genetic algorithm was introduced into the optimal design of CTA interior ballistics with coupling the CTA interior ballistic model. Aiming at the interior ballistic characteristics of a CTA gun, the goal of CTA interior ballistic design is to obtain a projectile velocity as large as possible. The optimal design of CTA interior ballistic is carried out using a genetic algorithm by setting peak pressure, changing the chamber volume and gun powder charge density. A numerical simulation of interior ballistics based on a 35 mm CTA firing experimental scheme was conducted and then the genetic algorithm was used for numerical optimization. The projectile muzzle velocity of the optimized scheme is increased from 1168 m/s for the initial experimental scheme to 1182 m/s. Then four optimization schemes were obtained with several independent optimization processes. The schemes were compared with each other and the difference between these schemes is small. The peak pressure and muzzle velocity of these schemes are almost the same. The result shows that the genetic algorithm is effective in the optimal design of the CTA interior ballistics. This work will be lay the foundation for further CTA interior ballistic design. Keywords: Cased telescoped ammunition, Interior ballistics, Gunpowder, Optimization genetic algorithm

Expert systems and their use in augmenting design optimization

Science.gov (United States)

Kidwell, G. H.; Eskey, M. A.

1985-01-01

The challenging requirements that are evolving for future aircraft demand that each design be optimally integrated, for the penalties imposed by nonoptimal performance are significant. Classic numerical optimization algorithms have been and will continue to be important tools for aircraft designers. These methods are, however, limited to certain categories of aircraft design variables, leaving the remainder to be determined by the user. A method that makes use of knowledge-based expert systems offers the potential for aiding the conceptual design process in a way that is similar to that of numerical optimization, except that it would address discrete, discontinuous, abstract, or any other unoptimized aspect of vehicle design and integration. Other unique capabilities such as automatic discovery and learning in design may also be achievable in the near term. This paper discusses current practice in conceptual aircraft design and knowledge-based systems, and how knowledge-based systems can be used in conceptual design.

Design and Optimization of Filament Wound Composite Pressure Vessels

NARCIS (Netherlands)

Zu, L.

2012-01-01

One of the most important issues for the design of filament-wound pressure vessels reflects on the determination of the most efficient meridian profiles and related fiber architectures, leading to optimal structural performance. To better understand the design and optimization of filament-wound

The design of the run Clever randomized trial

DEFF Research Database (Denmark)

Ramskov, Daniel; Nielsen, Rasmus Oestergaard; Sørensen, Henrik

2016-01-01

BACKGROUND: Injury incidence and prevalence in running populations have been investigated and documented in several studies. However, knowledge about injury etiology and prevention is needed. Training errors in running are modifiable risk factors and people engaged in recreational running need...... evidence-based running schedules to minimize the risk of injury. The existing literature on running volume and running intensity and the development of injuries show conflicting results. This may be related to previously applied study designs, methods used to quantify the performed running...... and the statistical analysis of the collected data. The aim of the Run Clever trial is to investigate if a focus on running intensity compared with a focus on running volume in a running schedule influences the overall injury risk differently. METHODS/DESIGN: The Run Clever trial is a randomized trial with a 24-week...

Optimal Design of a Centrifugal Compressor Impeller Using Evolutionary Algorithms

Directory of Open Access Journals (Sweden)

Soo-Yong Cho

2012-01-01

Full Text Available An optimization study was conducted on a centrifugal compressor. Eight design variables were chosen from the control points for the Bezier curves which widely influenced the geometric variation; four design variables were selected to optimize the flow passage between the hub and the shroud, and other four design variables were used to improve the performance of the impeller blade. As an optimization algorithm, an artificial neural network (ANN was adopted. Initially, the design of experiments was applied to set up the initial data space of the ANN, which was improved during the optimization process using a genetic algorithm. If a result of the ANN reached a higher level, that result was re-calculated by computational fluid dynamics (CFD and was applied to develop a new ANN. The prediction difference between the ANN and CFD was consequently less than 1% after the 6th generation. Using this optimization technique, the computational time for the optimization was greatly reduced and the accuracy of the optimization algorithm was increased. The efficiency was improved by 1.4% without losing the pressure ratio, and Pareto-optimal solutions of the efficiency versus the pressure ratio were obtained through the 21st generation.

Crashworthiness design of transient frame structures using topology optimization

DEFF Research Database (Denmark)

Pedersen, Claus B. Wittendorf

2004-01-01

The aim of this paper is to present topology optimization as a method to obtain conceptual designs for crash-worthiness. The topology optimization formulation uses rigorously computed sensitivities. The large displacements and plasticity of the 2D beam elements are modelled with the co-rotational......The aim of this paper is to present topology optimization as a method to obtain conceptual designs for crash-worthiness. The topology optimization formulation uses rigorously computed sensitivities. The large displacements and plasticity of the 2D beam elements are modelled with the co...

Cost-Optimal Analysis for Nearly Zero Energy Buildings Design and Optimization: A Critical Review

Directory of Open Access Journals (Sweden)

Maria Ferrara

2018-06-01

Full Text Available Since the introduction of the recast of the EPBD European Directive 2010/31/EU, many studies on the cost-effective feasibility of nearly zero-energy buildings (NZEBs were carried out either by academic research bodies and by national bodies. In particular, the introduction of the cost-optimal methodology has given a strong impulse to research in this field. This paper presents a comprehensive and significant review on scientific works based on the application of cost-optimal analysis applications in Europe since the EPBD recast entered into force, pointing out the differences in the analyzed studies and comparing their outcomes before the new recast of EPBD enters into force in 2018. The analysis is conducted with special regard to the methods used for the energy performance assessment, the global cost calculation, and for the selection of the energy efficiency measures leading to design optimization. A critical discussion about the assumptions on which the studies are based and the resulting gaps between the resulting cost-optimal performance and the zero energy target is provided together with a summary of the resulting cost-optimal set of technologies to be used for cost-optimal NZEB design in different contexts. It is shown that the cost-optimal approach results as an effective method for delineating the future of NZEB design throughout Europe while emerging criticalities and open research issues are presented.

Multidisciplinary Aerospace Systems Optimization: Computational AeroSciences (CAS) Project

Science.gov (United States)

Kodiyalam, S.; Sobieski, Jaroslaw S. (Technical Monitor)

2001-01-01

The report describes a method for performing optimization of a system whose analysis is so expensive that it is impractical to let the optimization code invoke it directly because excessive computational cost and elapsed time might result. In such situation it is imperative to have user control the number of times the analysis is invoked. The reported method achieves that by two techniques in the Design of Experiment category: a uniform dispersal of the trial design points over a n-dimensional hypersphere and a response surface fitting, and the technique of krigging. Analyses of all the trial designs whose number may be set by the user are performed before activation of the optimization code and the results are stored as a data base. That code is then executed and referred to the above data base. Two applications, one of the airborne laser system, and one of an aircraft optimization illustrate the method application.

Instrument design and optimization using genetic algorithms

International Nuclear Information System (INIS)

Hoelzel, Robert; Bentley, Phillip M.; Fouquet, Peter

2006-01-01

This article describes the design of highly complex physical instruments by using a canonical genetic algorithm (GA). The procedure can be applied to all instrument designs where performance goals can be quantified. It is particularly suited to the optimization of instrument design where local optima in the performance figure of merit are prevalent. Here, a GA is used to evolve the design of the neutron spin-echo spectrometer WASP which is presently being constructed at the Institut Laue-Langevin, Grenoble, France. A comparison is made between this artificial intelligence approach and the traditional manual design methods. We demonstrate that the search of parameter space is more efficient when applying the genetic algorithm, and the GA produces a significantly better instrument design. Furthermore, it is found that the GA increases flexibility, by facilitating the reoptimization of the design after changes in boundary conditions during the design phase. The GA also allows the exploration of 'nonstandard' magnet coil geometries. We conclude that this technique constitutes a powerful complementary tool for the design and optimization of complex scientific apparatus, without replacing the careful thought processes employed in traditional design methods

Instrument design and optimization using genetic algorithms

Science.gov (United States)

Hölzel, Robert; Bentley, Phillip M.; Fouquet, Peter

2006-10-01

This article describes the design of highly complex physical instruments by using a canonical genetic algorithm (GA). The procedure can be applied to all instrument designs where performance goals can be quantified. It is particularly suited to the optimization of instrument design where local optima in the performance figure of merit are prevalent. Here, a GA is used to evolve the design of the neutron spin-echo spectrometer WASP which is presently being constructed at the Institut Laue-Langevin, Grenoble, France. A comparison is made between this artificial intelligence approach and the traditional manual design methods. We demonstrate that the search of parameter space is more efficient when applying the genetic algorithm, and the GA produces a significantly better instrument design. Furthermore, it is found that the GA increases flexibility, by facilitating the reoptimization of the design after changes in boundary conditions during the design phase. The GA also allows the exploration of "nonstandard" magnet coil geometries. We conclude that this technique constitutes a powerful complementary tool for the design and optimization of complex scientific apparatus, without replacing the careful thought processes employed in traditional design methods.

A pivotal registration phase III, multicenter, randomized tuberculosis controlled trial: design issues and lessons learnt from the Gatifloxacin for TB (OFLOTUB project

Directory of Open Access Journals (Sweden)

Merle Corinne SC

2012-05-01

Full Text Available Abstract Background There have been no major advances in tuberculosis (TB drug development since the first East African/British Medical Research Council short course chemotherapy trial 35 years ago. Since then, the landscape for conducting TB clinical trials has profoundly changed with the emergence of HIV infection, the spread of resistant TB bacilli strains, recent advances in mycobacteriological capacity, and drug discovery. As a consequence questions have arisen on the most appropriate approach to design and conduct current TB trials. To highlight key issues discussed: Is a superiority, equivalence, or non-inferiority design most appropriate? What should be the primary efficacy outcome? How to consider re-infections in the definition of the outcome? What is the optimal length of patient follow-up? Is blinding appropriate when treatment duration in test arm is shorter? What are the appropriate assumptions for sample size calculation? Methods Various drugs are currently in the development pipeline. We are presenting in this paper the design of the most recently completed phase III TB trial, the OFLOTUB project, which is the pivotal trial of a registration portfolio for a gatifloxacin-containing TB regimen. It is a randomized, open-label, multicenter, controlled trial aiming to evaluate the efficacy and safety of a gatifloxacin-containing 4-month regimen (trial registration: ClinicalTrial.gov database: NCT00216385. Results In the light of the recent scientific and regulatory discussions, we discuss some of the design issues in TB clinical trials and more specifically the reasons that guided our choices, in order to best answer the trial objectives, while at the same time satisfying regulatory authority requirements. Conclusion When shortening TB treatment, we are advocating for a non-inferiority, non-blinded design, with a composite unfavorable endpoint assessed 12 months post treatment completion, and added trial procedures specifically

Rotor design optimization using a free wake analysis

Science.gov (United States)

Quackenbush, Todd R.; Boschitsch, Alexander H.; Wachspress, Daniel A.; Chua, Kiat

1993-01-01

The aim of this effort was to develop a comprehensive performance optimization capability for tiltrotor and helicopter blades. The analysis incorporates the validated EHPIC (Evaluation of Hover Performance using Influence Coefficients) model of helicopter rotor aerodynamics within a general linear/quadratic programming algorithm that allows optimization using a variety of objective functions involving the performance. The resulting computer code, EHPIC/HERO (HElicopter Rotor Optimization), improves upon several features of the previous EHPIC performance model and allows optimization utilizing a wide spectrum of design variables, including twist, chord, anhedral, and sweep. The new analysis supports optimization of a variety of objective functions, including weighted measures of rotor thrust, power, and propulsive efficiency. The fundamental strength of the approach is that an efficient search for improved versions of the baseline design can be carried out while retaining the demonstrated accuracy inherent in the EHPIC free wake/vortex lattice performance analysis. Sample problems are described that demonstrate the success of this approach for several representative rotor configurations in hover and axial flight. Features that were introduced to convert earlier demonstration versions of this analysis into a generally applicable tool for researchers and designers is also discussed.

Application of colony complex algorithm to nuclear component optimization design

International Nuclear Information System (INIS)

Yan Changqi; Li Guijing; Wang Jianjun

2014-01-01

Complex algorithm (CA) has got popular application to the region of nuclear engineering. In connection with the specific features of the application of traditional complex algorithm (TCA) to the optimization design in engineering structures, an improved method, colony complex algorithm (CCA), was developed based on the optimal combination of many complexes, in which the disadvantages of TCA were overcame. The optimized results of benchmark function show that CCA has better optimizing performance than TCA. CCA was applied to the high-pressure heater optimization design, and the optimization effect is obvious. (authors)

Stress-constrained topology optimization for compliant mechanism design

DEFF Research Database (Denmark)

de Leon, Daniel M.; Alexandersen, Joe; Jun, Jun S.

2015-01-01

This article presents an application of stress-constrained topology optimization to compliant mechanism design. An output displacement maximization formulation is used, together with the SIMP approach and a projection method to ensure convergence to nearly discrete designs. The maximum stress...... is approximated using a normalized version of the commonly-used p-norm of the effective von Mises stresses. The usual problems associated with topology optimization for compliant mechanism design: one-node and/or intermediate density hinges are alleviated by the stress constraint. However, it is also shown...

Clinical Trials

Medline Plus

Full Text Available ... questions and clinical trials. Optimizing our Clinical Trials Enterprise NHLBI has a strong tradition of supporting clinical ... multi-pronged approach to Optimize our Clinical Trials Enterprise that will make our clinical trials enterprise even ...

On the construction of experimental designs for a given task by jointly optimizing several quality criteria: Pareto-optimal experimental designs.

Science.gov (United States)

Sánchez, M S; Sarabia, L A; Ortiz, M C

2012-11-19

Experimental designs for a given task should be selected on the base of the problem being solved and of some criteria that measure their quality. There are several such criteria because there are several aspects to be taken into account when making a choice. The most used criteria are probably the so-called alphabetical optimality criteria (for example, the A-, E-, and D-criteria related to the joint estimation of the coefficients, or the I- and G-criteria related to the prediction variance). Selecting a proper design to solve a problem implies finding a balance among these several criteria that measure the performance of the design in different aspects. Technically this is a problem of multi-criteria optimization, which can be tackled from different views. The approach presented here addresses the problem in its real vector nature, so that ad hoc experimental designs are generated with an algorithm based on evolutionary algorithms to find the Pareto-optimal front. There is not theoretical limit to the number of criteria that can be studied and, contrary to other approaches, no just one experimental design is computed but a set of experimental designs all of them with the property of being Pareto-optimal in the criteria needed by the user. Besides, the use of an evolutionary algorithm makes it possible to search in both continuous and discrete domains and avoid the need of having a set of candidate points, usual in exchange algorithms. Copyright © 2012 Elsevier B.V. All rights reserved.

Use of Experimental Design for Peuhl Cheese Process Optimization ...

African Journals Online (AJOL)

Use of Experimental Design for Peuhl Cheese Process Optimization. ... Journal of Applied Sciences and Environmental Management ... This work consisting in use of a central composite design enables the determination of optimal process conditions concerning: leaf extract volume added (7 mL), heating temperature ...

Developing an Integrated Design Strategy for Chip Layout Optimization

NARCIS (Netherlands)

Wits, Wessel Willems; Jauregui Becker, Juan Manuel; van Vliet, Frank Edward; te Riele, G.J.

2011-01-01

This paper presents an integrated design strategy for chip layout optimization. The strategy couples both electric and thermal aspects during the conceptual design phase to improve chip performances; thermal management being one of the major topics. The layout of the chip circuitry is optimized

Scalable and near-optimal design space exploration for embedded systems

CERN Document Server

Kritikakou, Angeliki; Goutis, Costas

2014-01-01

This book describes scalable and near-optimal, processor-level design space exploration (DSE) methodologies.  The authors present design methodologies for data storage and processing in real-time, cost-sensitive data-dominated embedded systems.  Readers will be enabled to reduce time-to-market, while satisfying system requirements for performance, area, and energy consumption, thereby minimizing the overall cost of the final design.   • Describes design space exploration (DSE) methodologies for data storage and processing in embedded systems, which achieve near-optimal solutions with scalable exploration time; • Presents a set of principles and the processes which support the development of the proposed scalable and near-optimal methodologies; • Enables readers to apply scalable and near-optimal methodologies to the intra-signal in-place optimization step for both regular and irregular memory accesses.

Optimizing the design of international safeguards inspection systems

International Nuclear Information System (INIS)

Markin, J.T.; Coulter, C.A.; Gutmacher, R.G.; Whitty, W.J.

1983-01-01

Efficient implementation of international inspections for verifying the operation of a nuclear facility requires that available resources be allocated among inspection activities to maximize detection of misoperation. This report describes a design and evaluation method for selecting an inspection system that is optimal for accomplishing inspection objectives. The discussion includes methods for identifying system objectives, defining performance measures, and choosing between candidate systems. Optimization theory is applied in selecting the most preferred inspection design for a single nuclear facility, and an extension to optimal allocation of inspection resources among States containing multiple facilities is outlined. 3 figures, 5 tables

Using pilot data to size a two-arm randomized trial to find a nearly optimal personalized treatment strategy.

Science.gov (United States)

Laber, Eric B; Zhao, Ying-Qi; Regh, Todd; Davidian, Marie; Tsiatis, Anastasios; Stanford, Joseph B; Zeng, Donglin; Song, Rui; Kosorok, Michael R

2016-04-15

A personalized treatment strategy formalizes evidence-based treatment selection by mapping patient information to a recommended treatment. Personalized treatment strategies can produce better patient outcomes while reducing cost and treatment burden. Thus, among clinical and intervention scientists, there is a growing interest in conducting randomized clinical trials when one of the primary aims is estimation of a personalized treatment strategy. However, at present, there are no appropriate sample size formulae to assist in the design of such a trial. Furthermore, because the sampling distribution of the estimated outcome under an estimated optimal treatment strategy can be highly sensitive to small perturbations in the underlying generative model, sample size calculations based on standard (uncorrected) asymptotic approximations or computer simulations may not be reliable. We offer a simple and robust method for powering a single stage, two-armed randomized clinical trial when the primary aim is estimating the optimal single stage personalized treatment strategy. The proposed method is based on inverting a plugin projection confidence interval and is thereby regular and robust to small perturbations of the underlying generative model. The proposed method requires elicitation of two clinically meaningful parameters from clinical scientists and uses data from a small pilot study to estimate nuisance parameters, which are not easily elicited. The method performs well in simulated experiments and is illustrated using data from a pilot study of time to conception and fertility awareness. Copyright © 2015 John Wiley & Sons, Ltd.

Optimal design of a hybridization scheme with a fuel cell using genetic optimization

Science.gov (United States)

Rodriguez, Marco A.

Fuel cell is one of the most dependable "green power" technologies, readily available for immediate application. It enables direct conversion of hydrogen and other gases into electric energy without any pollution of the environment. However, the efficient power generation is strictly stationary process that cannot operate under dynamic environment. Consequently, fuel cell becomes practical only within a specially designed hybridization scheme, capable of power storage and power management functions. The resultant technology could be utilized to its full potential only when both the fuel cell element and the entire hybridization scheme are optimally designed. The design optimization in engineering is among the most complex computational tasks due to its multidimensionality, nonlinearity, discontinuity and presence of constraints in the underlying optimization problem. this research aims at the optimal utilization of the fuel cell technology through the use of genetic optimization, and advance computing. This study implements genetic optimization in the definition of optimum hybridization rules for a PEM fuel cell/supercapacitor power system. PEM fuel cells exhibit high energy density but they are not intended for pulsating power draw applications. They work better in steady state operation and thus, are often hybridized. In a hybrid system, the fuel cell provides power during steady state operation while capacitors or batteries augment the power of the fuel cell during power surges. Capacitors and batteries can also be recharged when the motor is acting as a generator. Making analogies to driving cycles, three hybrid system operating modes are investigated: 'Flat' mode, 'Uphill' mode, and 'Downhill' mode. In the process of discovering the switching rules for these three modes, we also generate a model of a 30W PEM fuel cell. This study also proposes the optimum design of a 30W PEM fuel cell. The PEM fuel cell model and hybridization's switching rules are postulated

Kriging-based algorithm for nuclear reactor neutronic design optimization

International Nuclear Information System (INIS)

Kempf, Stephanie; Forget, Benoit; Hu, Lin-Wen

2012-01-01

Highlights: ► A Kriging-based algorithm was selected to guide research reactor optimization. ► We examined impacts of parameter values upon the algorithm. ► The best parameter values were incorporated into a set of best practices. ► Algorithm with best practices used to optimize thermal flux of concept. ► Final design produces thermal flux 30% higher than other 5 MW reactors. - Abstract: Kriging, a geospatial interpolation technique, has been used in the present work to drive a search-and-optimization algorithm which produces the optimum geometric parameters for a 5 MW research reactor design. The technique has been demonstrated to produce an optimal neutronic solution after a relatively small number of core calculations. It has additionally been successful in producing a design which significantly improves thermal neutron fluxes by 30% over existing reactors of the same power rating. Best practices for use of this algorithm in reactor design were identified and indicated the importance of selecting proper correlation functions.

Study on Design Optimization of Centrifugal Compressors Considering Efficiency and Weight

International Nuclear Information System (INIS)

Lee, Younghwan; Kang, Shinhyoung; Ha, Kyunggu

2015-01-01

Various centrifugal compressors are currently used extensively in industrial fields, where the design requirements are more complicated. This makes it more difficult to determine the optimal design point of a centrifugal compressor. Traditionally, the efficiency is an important factor for optimization. In this study, the weight of the compressor was also considered. The aim of this study was to present the design tendency considering the stage efficiency and weight. In addition, this study suggested possibility of a selection of compressor design objectives at an early design stage based on the optimization results. Only a vaneless diffuser was considered in this case. The Kriging method was used with sample points from 1D design program data. The optimal points were determined in a substitute design space.

Study on Design Optimization of Centrifugal Compressors Considering Efficiency and Weight

Energy Technology Data Exchange (ETDEWEB)

Lee, Younghwan; Kang, Shinhyoung [Seoul National University, Seoul (Korea, Republic of); Ha, Kyunggu [Hyundai Motor Group, Ulsan (Korea, Republic of)

2015-04-15

Various centrifugal compressors are currently used extensively in industrial fields, where the design requirements are more complicated. This makes it more difficult to determine the optimal design point of a centrifugal compressor. Traditionally, the efficiency is an important factor for optimization. In this study, the weight of the compressor was also considered. The aim of this study was to present the design tendency considering the stage efficiency and weight. In addition, this study suggested possibility of a selection of compressor design objectives at an early design stage based on the optimization results. Only a vaneless diffuser was considered in this case. The Kriging method was used with sample points from 1D design program data. The optimal points were determined in a substitute design space.

Group sequential and confirmatory adaptive designs in clinical trials

CERN Document Server

Wassmer, Gernot

2016-01-01

This book provides an up-to-date review of the general principles of and techniques for confirmatory adaptive designs. Confirmatory adaptive designs are a generalization of group sequential designs. With these designs, interim analyses are performed in order to stop the trial prematurely under control of the Type I error rate. In adaptive designs, it is also permissible to perform a data-driven change of relevant aspects of the study design at interim stages. This includes, for example, a sample-size reassessment, a treatment-arm selection or a selection of a pre-specified sub-population. Essentially, this adaptive methodology was introduced in the 1990s. Since then, it has become popular and the object of intense discussion and still represents a rapidly growing field of statistical research. This book describes adaptive design methodology at an elementary level, while also considering designing and planning issues as well as methods for analyzing an adaptively planned trial. This includes estimation methods...

Optimizing Intermodal Train Schedules with a Design Balanced Network Design Model

DEFF Research Database (Denmark)

Pedersen, Michael Berliner; Crainic, Teodor Gabriel

We present a modeling approach for optimizing intermodal trains schedules based on an infrastructure divided into time-dependent train paths. The formulation can be generalized to a capacitated multi commodity network design model with additional design balance constraints. We present a Tabu Search...

Asteroid Rendezvous Mission Design Using Multiobjective Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Ya-zhong Luo

2014-01-01

Full Text Available A new preliminary trajectory design method for asteroid rendezvous mission using multiobjective optimization techniques is proposed. This method can overcome the disadvantages of the widely employed Pork-Chop method. The multiobjective integrated launch window and multi-impulse transfer trajectory design model is formulated, which employes minimum-fuel cost and minimum-time transfer as two objective functions. The multiobjective particle swarm optimization (MOPSO is employed to locate the Pareto solution. The optimization results of two different asteroid mission designs show that the proposed approach can effectively and efficiently demonstrate the relations among the mission characteristic parameters such as launch time, transfer time, propellant cost, and number of maneuvers, which will provide very useful reference for practical asteroid mission design. Compared with the PCP method, the proposed approach is demonstrated to be able to provide much more easily used results, obtain better propellant-optimal solutions, and have much better efficiency. The MOPSO shows a very competitive performance with respect to the NSGA-II and the SPEA-II; besides a proposed boundary constraint optimization strategy is testified to be able to improve its performance.

Optimization and characterization of liposome formulation by mixture design.

Science.gov (United States)

Maherani, Behnoush; Arab-tehrany, Elmira; Kheirolomoom, Azadeh; Reshetov, Vadzim; Stebe, Marie José; Linder, Michel

2012-02-07

This study presents the application of the mixture design technique to develop an optimal liposome formulation by using the different lipids in type and percentage (DOPC, POPC and DPPC) in liposome composition. Ten lipid mixtures were generated by the simplex-centroid design technique and liposomes were prepared by the extrusion method. Liposomes were characterized with respect to size, phase transition temperature, ζ-potential, lamellarity, fluidity and efficiency in loading calcein. The results were then applied to estimate the coefficients of mixture design model and to find the optimal lipid composition with improved entrapment efficiency, size, transition temperature, fluidity and ζ-potential of liposomes. The response optimization of experiments was the liposome formulation with DOPC: 46%, POPC: 12% and DPPC: 42%. The optimal liposome formulation had an average diameter of 127.5 nm, a phase-transition temperature of 11.43 °C, a ζ-potential of -7.24 mV, fluidity (1/P)(TMA-DPH)((¬)) value of 2.87 and an encapsulation efficiency of 20.24%. The experimental results of characterization of optimal liposome formulation were in good agreement with those predicted by the mixture design technique.

Optimization of Loudspeaker Part Design Parameters by Air Viscosity Damping Effect

OpenAIRE

Yue Hu; Xilu Zhao; Takao Yamaguchi; Manabu Sasajima; Yoshio Koike; Akira Hara

2016-01-01

This study optimized the design parameters of a cone loudspeaker as an example of high flexibility of the product design. We developed an acoustic analysis software program that considers the impact of damping caused by air viscosity. In sound reproduction, it is difficult to optimize each parameter of the loudspeaker design. To overcome the limitation of the design problem in practice, this study presents an acoustic analysis algorithm to optimize the design parameters of the loudspeaker. Th...

Analytical Model-Based Design Optimization of a Transverse Flux Machine

Energy Technology Data Exchange (ETDEWEB)

Hasan, Iftekhar; Husain, Tausif; Sozer, Yilmaz; Husain, Iqbal; Muljadi, Eduard

2017-02-16

This paper proposes an analytical machine design tool using magnetic equivalent circuit (MEC)-based particle swarm optimization (PSO) for a double-sided, flux-concentrating transverse flux machine (TFM). The magnetic equivalent circuit method is applied to analytically establish the relationship between the design objective and the input variables of prospective TFM designs. This is computationally less intensive and more time efficient than finite element solvers. A PSO algorithm is then used to design a machine with the highest torque density within the specified power range along with some geometric design constraints. The stator pole length, magnet length, and rotor thickness are the variables that define the optimization search space. Finite element analysis (FEA) was carried out to verify the performance of the MEC-PSO optimized machine. The proposed analytical design tool helps save computation time by at least 50% when compared to commercial FEA-based optimization programs, with results found to be in agreement with less than 5% error.

Optimal design of robust piezoelectric unimorph microgrippers

DEFF Research Database (Denmark)

Ruiz, David; Díaz-Molina, Alex; Sigmund, Ole

2018-01-01

Topology optimization can be used to design piezoelectric actuators by simultaneous design of host structure and polarization profile. Subsequent micro-scale fabrication leads us to overcome important manufacturing limitations: difficulties in placing a piezoelectric layer on both top and bottom...

Optimization design of solar enhanced natural draft dry cooling tower

International Nuclear Information System (INIS)

Zou, Zheng; Guan, Zhiqiang; Gurgenci, Hal

2013-01-01

Highlights: • We proposed a cost model for solar enhanced natural draft dry cooling tower. • We proposed an optimization scheme for this new cooling system. • We optimally designed one for a 50 MW EGS geothermal plant as a demonstration. • Results proved its economic advantages for EGS geothermal application. - Abstract: This paper proposed an optimization scheme for solar enhanced natural draft dry cooling tower design, in which a detailed cost model was proposed including capital, labour, maintenance and operation costs of each component. Based on the developed cost model, the optimal design option can be identified in terms of the relatively lower annual cost and the relatively higher total extra income over the Solar Enhanced Natural Draft Dry Cooling Tower (SENDDCT) lifetime. As a case study, a SENDDCT was optimally designed to meet the cooling demand for a 50 MW geothermal power plant with Engineered Geothermal System (EGS) technology. The results showed that the optimized SENDDCT not only has better cooling performance during the daytime but also is a cost effective option for EGS geothermal power plants

Standards for Clinical Trials in Male and Female Sexual Dysfunction: I. Phase I to Phase IV Clinical Trial Design.

Science.gov (United States)

Fisher, William A; Gruenwald, Ilan; Jannini, Emmanuele A; Lev-Sagie, Ahinoam; Lowenstein, Lior; Pyke, Robert E; Reisman, Yakov; Revicki, Dennis A; Rubio-Aurioles, Eusebio

2016-12-01

This series of articles outlines standards for clinical trials of treatments for male and female sexual dysfunctions, with a focus on research design and patient-reported outcome assessment. These articles consist of revision, updating, and integration of articles on standards for clinical trials in male and female sexual dysfunction from the 2010 International Consultation on Sexual Medicine developed by the authors as part of the 2015 International Consultation on Sexual Medicine. We are guided in this effort by several principles. In contrast to previous versions of these guidelines, we merge discussion of standards for clinical trials in male and female sexual dysfunction in an integrated approach that emphasizes the common foundational practices that underlie clinical trials in the two settings. We present a common expected standard for clinical trial design in male and female sexual dysfunction, a common rationale for the design of phase I to IV clinical trials, and common considerations for selection of study population and study duration in male and female sexual dysfunction. We present a focused discussion of fundamental principles in patient- (and partner-) reported outcome assessment and complete this series of articles with specific discussions of selected aspects of clinical trials that are unique to male and to female sexual dysfunction. Our consideration of standards for clinical trials in male and female sexual dysfunction attempts to embody sensitivity to existing and new regulatory guidance and to address implications of the evolution of the diagnosis of sexual dysfunction that have been brought forward in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. The first article in this series focuses on phase I to phase IV clinical trial design considerations. Subsequent articles in this series focus on the measurement of patient-reported outcomes, unique aspects of clinical trial design for men, and unique aspects of clinical

DESIGN OPTIMIZATION OF A FOOT VALVE BY USING ANSYS®

Directory of Open Access Journals (Sweden)

Serdar KARAOĞLU

2008-02-01

Full Text Available In this study, main components of a foot valve, being produced by casting, were optimized for minimum weight. The study was focused on the minimization of casting costs by reducing the volumes of two main parts of the foot valve. ANSYS® finite elements package was used in the study. In the optimization stage, parametrical dimensions were determined according to manufacturer's design criteria and related standards. Final design of the foot valve was completed by using the calculated values of optimum dimensions of the main components. Design optimization procedure gave about 8.5% of weight reductions in the main foot valve components.

Structural Optimization Design of Horizontal-Axis Wind Turbine Blades Using a Particle Swarm Optimization Algorithm and Finite Element Method

Directory of Open Access Journals (Sweden)

Pan Pan

2012-11-01

Full Text Available This paper presents an optimization method for the structural design of horizontal-axis wind turbine (HAWT blades based on the particle swarm optimization algorithm (PSO combined with the finite element method (FEM. The main goal is to create an optimization tool and to demonstrate the potential improvements that could be brought to the structural design of HAWT blades. A multi-criteria constrained optimization design model pursued with respect to minimum mass of the blade is developed. The number and the location of layers in the spar cap and the positions of the shear webs are employed as the design variables, while the strain limit, blade/tower clearance limit and vibration limit are taken into account as the constraint conditions. The optimization of the design of a commercial 1.5 MW HAWT blade is carried out by combining the above method and design model under ultimate (extreme flap-wise load conditions. The optimization results are described and compared with the original design. It shows that the method used in this study is efficient and produces improved designs.

OPTIMAL NETWORK TOPOLOGY DESIGN

Science.gov (United States)

Yuen, J. H.

1994-01-01

This program was developed as part of a research study on the topology design and performance analysis for the Space Station Information System (SSIS) network. It uses an efficient algorithm to generate candidate network designs (consisting of subsets of the set of all network components) in increasing order of their total costs, and checks each design to see if it forms an acceptable network. This technique gives the true cost-optimal network, and is particularly useful when the network has many constraints and not too many components. It is intended that this new design technique consider all important performance measures explicitly and take into account the constraints due to various technical feasibilities. In the current program, technical constraints are taken care of by the user properly forming the starting set of candidate components (e.g. nonfeasible links are not included). As subsets are generated, they are tested to see if they form an acceptable network by checking that all requirements are satisfied. Thus the first acceptable subset encountered gives the cost-optimal topology satisfying all given constraints. The user must sort the set of "feasible" link elements in increasing order of their costs. The program prompts the user for the following information for each link: 1) cost, 2) connectivity (number of stations connected by the link), and 3) the stations connected by that link. Unless instructed to stop, the program generates all possible acceptable networks in increasing order of their total costs. The program is written only to generate topologies that are simply connected. Tests on reliability, delay, and other performance measures are discussed in the documentation, but have not been incorporated into the program. This program is written in PASCAL for interactive execution and has been implemented on an IBM PC series computer operating under PC DOS. The disk contains source code only. This program was developed in 1985.

DESIGN OPTIMIZATION METHOD USED IN MECHANICAL ENGINEERING

Directory of Open Access Journals (Sweden)

SCURTU Iacob Liviu

2016-11-01

Full Text Available This paper presents an optimization study in mechanical engineering. First part of the research describe the structural optimization method used, followed by the presentation of several optimization studies conducted in recent years. The second part of the paper presents the CAD modelling of an agricultural plough component. The beam of the plough is analysed using finite element method. The plough component is meshed in solid elements, and the load case which mimics the working conditions of agricultural equipment of this are created. The model is prepared to find the optimal structural design, after the FEA study of the model is done. The mass reduction of part is the criterion applied for this optimization study. The end of this research presents the final results and the model optimized shape.

The utility of screening in the design of trials for symptom management in cancer.

Science.gov (United States)

Jeon, Sangchoon; Given, Charles W; Sikorskii, Alla; Given, Barbara

2009-10-01

Clinical trials that test interventions for symptom management must target patients whose symptoms are severe and can benefit from participation. Screening symptoms for their severity prior to trial entry may be an important element of trial design. This research describes the utility of screening for severity of symptoms prior to entry into clinical trials for symptom management in cancer. To accomplish this, 601 cancer patients undergoing chemotherapy were assessed at screening and at the initial intervention contact, using the 0-10 rating scale for severity of nine symptoms. Post-test probabilities and likelihood ratios (LRs) were estimated across cut-offs in screening severity scores. Areas under receiver operating characteristic curves for reaching threshold of four at the initial intervention contact were estimated by a nonparametric method. It was found that screening severity scores were good predictors for identifying patients who would not reach threshold but did not always accurately predict patients who would. The cut-offs between 2 and 4 on a 0-10 scale could be used to identify patients that might benefit from receipt of interventions. For all symptoms, the LRs were greater than one across possible screening cut-offs. The findings indicate that decision rules based on screening prior to entry into cancer symptom management trials can provide reasonable discriminative accuracy by differentiating among patients who are likely to reach higher levels of severity later in the trial from those who are not. Optimal severity cut-offs can be established based on LRs and desired sensitivity and specificity.

Design optimization and uncertainty analysis of SMA morphing structures

International Nuclear Information System (INIS)

Oehler, S D; Hartl, D J; Lopez, R; Malak, R J; Lagoudas, D C

2012-01-01

The continuing implementation of shape memory alloys (SMAs) as lightweight solid-state actuators in morphing structures has now motivated research into finding optimized designs for use in aerospace control systems. This work proposes methods that use iterative analysis techniques to determine optimized designs for morphing aerostructures and consider the impact of uncertainty in model variables on the solution. A combination of commercially available and custom coded tools is utilized. ModelCenter, a suite of optimization algorithms and simulation process management tools, is coupled with the Abaqus finite element analysis suite and a custom SMA constitutive model to assess morphing structure designs in an automated fashion. The chosen case study involves determining the optimized configuration of a morphing aerostructure assembly that includes SMA flexures. This is accomplished by altering design inputs representing the placement of active components to minimize a specified cost function. An uncertainty analysis is also conducted using design of experiment methods to determine the sensitivity of the solution to a set of uncertainty variables. This second study demonstrates the effective use of Monte Carlo techniques to simulate the variance of model variables representing the inherent uncertainty in component fabrication processes. This paper outlines the modeling tools used to execute each case study, details the procedures for constructing the optimization problem and uncertainty analysis, and highlights the results from both studies. (paper)

Methods for the Design of Vasomotor Symptom Trials: The MsFLASH Network

Science.gov (United States)

Newton, Katherine M.; Carpenter, Janet S.; Guthrie, Katherine A.; Anderson, Garnet L.; Caan, Bette; Cohen, Lee S.; Ensrud, Kristine E.; Freeman, Ellen W.; Joffe, Hadine; Sternfeld, Barbara; Reed, Susan D.; Sherman, Sheryl; Sammel, Mary D.; Kroenke, Kurt; Larson, Joseph C.; LaCroix, Andrea Z.

2013-01-01

Objective This report describes the "Menopausal Strategies: Finding Lasting Answers to Symptoms and Health” (MsFLASH) network and methodological issues addressed in designing and implementing vasomotor symptom trials. Methods Established in response to a National Institute of Health request for applications, the network was charged with conducting rapid throughput randomized trials of novel and understudied available interventions postulated to alleviate vasomotor and other menopausal symptoms. Included are descriptions of and rationale for criteria used for interventions and study selection, common eligibility and exclusion criteria, common primary and secondary outcome measures, consideration of placebo response, establishment of a biorepository, trial duration, screening and recruitment, statistical methods, and quality control. All trial designs are presented including: 1) a randomized, double-blind, placebo-controlled clinical trial designed to evaluate effectiveness of the selective serotonin reuptake inhibitor escitalopram in reducing vasomotor symptom frequency and severity; 2) a 2×3 factorial design trial to test three different interventions (yoga, exercise, and omega-3 supplementation) for improvement of vasomotor symptom frequency and bother; and 3) a three-arm comparative efficacy trial of the serotonin-norepinephrine reuptake inhibitor venlafaxine and low-dose oral estradiol versus placebo for reducing vasomotor symptom frequency compared to placebo. The network’s structure and governance are also discussed. Conclusions The methods used and lessons learned in the MsFLASH trials are shared to encourage and support the conduct of similar trials and encourage collaborations with other researchers. PMID:23760428

On fully stressed design and p-norm measures in structural optimization

DEFF Research Database (Denmark)

Zhou, Mingdong; Sigmund, Ole

2017-01-01

This brief note revisits the fully stressed design schemes and p-norm measures used in stress-based structural optimization. Two simple shape optimization cases are used to remind the reader that fully stressed designs only are optimal when unimpeded by geometrical restrictions and that high valu...... of the stress norm are needed in order to achieve satisfactory designs....

The optimal injection technique for the osteoarthritic ankle: A randomized, cross-over trial

NARCIS (Netherlands)

Witteveen, Angelique G. H.; Kok, Aimee; Sierevelt, Inger N.; Kerkhoffs, Gino M. M. J.; van Dijk, C. Niek

2013-01-01

Background: To optimize the injection technique for the osteoarthritic ankle in order to enhance the effect of intra-articular injections and minimize adverse events. Methods: Randomized cross-over trial. Comparing two injection techniques in patients with symptomatic ankle osteoarthritis. Patients

Lightweight design of a vertical articulated robot using topology optimization

Energy Technology Data Exchange (ETDEWEB)

Hong, Seong Ki; Hong, Jung Ki; Jang, Gang Won [Sejong Univ., Seoul (Korea, Republic of); Kim, Tae Hyun; Park, Jin Kyun; Kim, Sang Hyun [Hyundai Heavy Industries Co., Ltd., Daejeon (Korea, Republic of)

2012-12-15

Topology optimization is applied for the lightweight design of three main parts of a vertical articulated robot: a base frame, a lower and a upper frame. Design domains for optimization are set as large solid regions that completely embrace the original parts, which are discretized by using three dimensional solid elements. Design variables are parameterized one to one to the material properties of each element by using the SIMP method. The objective of optimization is set as the multi objective form combining the natural frequencies and mean compliances of a structure for which load steps of interest are selected from the multibody dynamics analysis of a robot. The obtained results of topology optimization are post processed to designs favorable to manufacturability for casting process. The final optimized results are 11.0% (base frame), 12.0% (lower frame) and 10.0% (upper frame) lighter with similar or even higher static and dynamic stiffnesses than the original models.

Design and optimization of flexible multi-generation systems

DEFF Research Database (Denmark)

Lythcke-Jørgensen, Christoffer Ernst

variations and dynamics, and energy system analysis, which fails to consider process integration synergies in local systems. The primary objective of the thesis is to derive a methodology for linking process design practices with energy system analysis for enabling coherent and holistic design optimization...... of flexible multi-generation system. In addition, the case study results emphasize the importance of considering flexible operation, systematic process integration, and systematic assessment of uncertainties in the design optimization. It is recommended that future research focus on assessing system impacts...... from flexible multi-generation systems and performance improvements from storage options....

Optimization Design and Application of Underground Reinforced Concrete Bifurcation Pipe

Directory of Open Access Journals (Sweden)

Chao Su

2015-01-01

Full Text Available Underground reinforced concrete bifurcation pipe is an important part of conveyance structure. During construction, the workload of excavation and concrete pouring can be significantly decreased according to optimized pipe structure, and the engineering quality can be improved. This paper presents an optimization mathematical model of underground reinforced concrete bifurcation pipe structure according to real working status of several common pipe structures from real cases. Then, an optimization design system was developed based on Particle Swarm Optimization algorithm. Furthermore, take the bifurcation pipe of one hydropower station as an example: optimization analysis was conducted, and accuracy and stability of the optimization design system were verified successfully.

Investigation of Navier-Stokes Code Verification and Design Optimization

Science.gov (United States)

Vaidyanathan, Rajkumar

2004-01-01

With rapid progress made in employing computational techniques for various complex Navier-Stokes fluid flow problems, design optimization problems traditionally based on empirical formulations and experiments are now being addressed with the aid of computational fluid dynamics (CFD). To be able to carry out an effective CFD-based optimization study, it is essential that the uncertainty and appropriate confidence limits of the CFD solutions be quantified over the chosen design space. The present dissertation investigates the issues related to code verification, surrogate model-based optimization and sensitivity evaluation. For Navier-Stokes (NS) CFD code verification a least square extrapolation (LSE) method is assessed. This method projects numerically computed NS solutions from multiple, coarser base grids onto a freer grid and improves solution accuracy by minimizing the residual of the discretized NS equations over the projected grid. In this dissertation, the finite volume (FV) formulation is focused on. The interplay between the xi concepts and the outcome of LSE, and the effects of solution gradients and singularities, nonlinear physics, and coupling of flow variables on the effectiveness of LSE are investigated. A CFD-based design optimization of a single element liquid rocket injector is conducted with surrogate models developed using response surface methodology (RSM) based on CFD solutions. The computational model consists of the NS equations, finite rate chemistry, and the k-6 turbulence closure. With the aid of these surrogate models, sensitivity and trade-off analyses are carried out for the injector design whose geometry (hydrogen flow angle, hydrogen and oxygen flow areas and oxygen post tip thickness) is optimized to attain desirable goals in performance (combustion length) and life/survivability (the maximum temperatures on the oxidizer post tip and injector face and a combustion chamber wall temperature). A preliminary multi-objective optimization

A proposal of optimal sampling design using a modularity strategy

Science.gov (United States)

Simone, A.; Giustolisi, O.; Laucelli, D. B.

2016-08-01

In real water distribution networks (WDNs) are present thousands nodes and optimal placement of pressure and flow observations is a relevant issue for different management tasks. The planning of pressure observations in terms of spatial distribution and number is named sampling design and it was faced considering model calibration. Nowadays, the design of system monitoring is a relevant issue for water utilities e.g., in order to manage background leakages, to detect anomalies and bursts, to guarantee service quality, etc. In recent years, the optimal location of flow observations related to design of optimal district metering areas (DMAs) and leakage management purposes has been faced considering optimal network segmentation and the modularity index using a multiobjective strategy. Optimal network segmentation is the basis to identify network modules by means of optimal conceptual cuts, which are the candidate locations of closed gates or flow meters creating the DMAs. Starting from the WDN-oriented modularity index, as a metric for WDN segmentation, this paper proposes a new way to perform the sampling design, i.e., the optimal location of pressure meters, using newly developed sampling-oriented modularity index. The strategy optimizes the pressure monitoring system mainly based on network topology and weights assigned to pipes according to the specific technical tasks. A multiobjective optimization minimizes the cost of pressure meters while maximizing the sampling-oriented modularity index. The methodology is presented and discussed using the Apulian and Exnet networks.

Optimization of reload core design for PWR

International Nuclear Information System (INIS)

Shen Wei; Xie Zhongsheng; Yin Banghua

1995-01-01

A direct efficient optimization technique has been effected for automatically optimizing the reload of PWR. The objective functions include: maximization of end-of-cycle (EOC) reactivity and maximization of average discharge burnup. The fuel loading optimization and burnable poison (BP) optimization are separated into two stages by using Haling principle. In the first stage, the optimum fuel reloading pattern without BP is determined by the linear programming method using enrichments as control variable, while in the second stage the optimum BP allocation is determined by the flexible tolerance method using the number of BP rods as control variable. A practical and efficient PWR reloading optimization program based on above theory has been encoded and successfully applied to Qinshan Nuclear Power Plant (QNP) cycle 2 reloading design

Optimization of coronagraph design for segmented aperture telescopes

Science.gov (United States)

Jewell, Jeffrey; Ruane, Garreth; Shaklan, Stuart; Mawet, Dimitri; Redding, Dave

2017-09-01

The goal of directly imaging Earth-like planets in the habitable zone of other stars has motivated the design of coronagraphs for use with large segmented aperture space telescopes. In order to achieve an optimal trade-off between planet light throughput and diffracted starlight suppression, we consider coronagraphs comprised of a stage of phase control implemented with deformable mirrors (or other optical elements), pupil plane apodization masks (gray scale or complex valued), and focal plane masks (either amplitude only or complex-valued, including phase only such as the vector vortex coronagraph). The optimization of these optical elements, with the goal of achieving 10 or more orders of magnitude in the suppression of on-axis (starlight) diffracted light, represents a challenging non-convex optimization problem with a nonlinear dependence on control degrees of freedom. We develop a new algorithmic approach to the design optimization problem, which we call the "Auxiliary Field Optimization" (AFO) algorithm. The central idea of the algorithm is to embed the original optimization problem, for either phase or amplitude (apodization) in various planes of the coronagraph, into a problem containing additional degrees of freedom, specifically fictitious "auxiliary" electric fields which serve as targets to inform the variation of our phase or amplitude parameters leading to good feasible designs. We present the algorithm, discuss details of its numerical implementation, and prove convergence to local minima of the objective function (here taken to be the intensity of the on-axis source in a "dark hole" region in the science focal plane). Finally, we present results showing application of the algorithm to both unobscured off-axis and obscured on-axis segmented telescope aperture designs. The application of the AFO algorithm to the coronagraph design problem has produced solutions which are capable of directly imaging planets in the habitable zone, provided end

Influence of reported study design characteristics on intervention effect estimates from randomized, controlled trials

DEFF Research Database (Denmark)

Savović, Jelena; Jones, Hayley E; Altman, Douglas G

2012-01-01

bias and increases in between-trial heterogeneity were driven primarily by trials with subjective outcomes, with little evidence of bias in trials with objective and mortality outcomes. This study is limited by incomplete trial reporting, and findings may be confounded by other study design...... characteristics. Bias associated with study design characteristics may lead to exaggeration of intervention effect estimates and increases in between-trial heterogeneity in trials reporting subjectively assessed outcomes....

Design and optimization of self-nanoemulsifying drug delivery systems for improved bioavailability of cyclovirobuxine D.

Science.gov (United States)

Ke, Zhongcheng; Hou, Xuefeng; Jia, Xiao-Bin

2016-01-01

The main purpose of this research was to design a self-nanoemulsifying drug delivery system (SNEDDS) for improving the bioavailability of cyclovirobuxine D as a poorly water-soluble drug. Solubility trials, emulsifying studies, and pseudo-ternary phase diagrams were used to screen the SNEDDS formulations. The optimized drug-loaded SNEDDS was prepared at a mass ratio of 3:24:38:38 for cyclovirobuxine D, oleic acid, Solutol SH15, and propylene glycol, respectively. The optimized formulation was characterized in terms of physicochemical and pharmacokinetic parameters compared with marketed cyclovirobuxine D tablets. The optimized cyclovirobuxine-D-loaded SNEDDS was spontaneously dispersed to form a nanoemulsion with a globule size of 64.80±3.58 nm, which exhibited significant improvement of drug solubility, rapid absorption rate, and enhanced area under the curve, together with increased permeation and decreased efflux. Fortunately, there was a nonsignificant cytotoxic effect toward Caco-2 cells. The relative bioavailability of SNEDDS was 200.22% in comparison with market tablets, in rabbits. SNEDDS could be a potential candidate for an oral dosage form of cyclovirobuxine D with improved bioavailability.

Performance indices and evaluation of algorithms in building energy efficient design optimization

International Nuclear Information System (INIS)

Si, Binghui; Tian, Zhichao; Jin, Xing; Zhou, Xin; Tang, Peng; Shi, Xing

2016-01-01

Building energy efficient design optimization is an emerging technique that is increasingly being used to design buildings with better overall performance and a particular emphasis on energy efficiency. To achieve building energy efficient design optimization, algorithms are vital to generate new designs and thus drive the design optimization process. Therefore, the performance of algorithms is crucial to achieving effective energy efficient design techniques. This study evaluates algorithms used for building energy efficient design optimization. A set of performance indices, namely, stability, robustness, validity, speed, coverage, and locality, is proposed to evaluate the overall performance of algorithms. A benchmark building and a design optimization problem are also developed. Hooke–Jeeves algorithm, Multi-Objective Genetic Algorithm II, and Multi-Objective Particle Swarm Optimization algorithm are evaluated by using the proposed performance indices and benchmark design problem. Results indicate that no algorithm performs best in all six areas. Therefore, when facing an energy efficient design problem, the algorithm must be carefully selected based on the nature of the problem and the performance indices that matter the most. - Highlights: • Six indices of algorithm performance in building energy optimization are developed. • For each index, its concept is defined and the calculation formulas are proposed. • A benchmark building and benchmark energy efficient design problem are proposed. • The performance of three selected algorithms are evaluated.

Crashworthiness design optimization using multipoint sequential linear programming

NARCIS (Netherlands)

Etman, L.F.P.; Adriaens, J.M.T.A.; Slagmaat, van M.T.P.; Schoofs, A.J.G.

1996-01-01

A design optimization tool has been developed for the crash victim simulation software MADYMO. The crash worthiness optimization problem is characterized by a noisy behaviour of objective function and constraints. Additionally, objective function and constraint values follow from a computationally

Optimal Design and Operation of Permanent Irrigation Systems

Science.gov (United States)

Oron, Gideon; Walker, Wynn R.

1981-01-01

Solid-set pressurized irrigation system design and operation are studied with optimization techniques to determine the minimum cost distribution system. The principle of the analysis is to divide the irrigation system into subunits in such a manner that the trade-offs among energy, piping, and equipment costs are selected at the minimum cost point. The optimization procedure involves a nonlinear, mixed integer approach capable of achieving a variety of optimal solutions leading to significant conclusions with regard to the design and operation of the system. Factors investigated include field geometry, the effect of the pressure head, consumptive use rates, a smaller flow rate in the pipe system, and outlet (sprinkler or emitter) discharge.

Enabling Parametric Optimal Ascent Trajectory Modeling During Early Phases of Design

Science.gov (United States)

Holt, James B.; Dees, Patrick D.; Diaz, Manuel J.

2015-01-01

During the early phases of engineering design, the costs committed are high, costs incurred are low, and the design freedom is high. It is well documented that decisions made in these early design phases drive the entire design's life cycle. In a traditional paradigm, key design decisions are made when little is known about the design. As the design matures, design changes become more difficult -- in both cost and schedule -- to enact. Indeed, the current capability-based paradigm that has emerged because of the constrained economic environment calls for the infusion of knowledge acquired during later design phases into earlier design phases, i.e. bring knowledge acquired during preliminary and detailed design into pre-conceptual and conceptual design. An area of critical importance to launch vehicle design is the optimization of its ascent trajectory, as the optimal trajectory will be able to take full advantage of the launch vehicle's capability to deliver a maximum amount of payload into orbit. Hence, the optimal ascent trajectory plays an important role in the vehicle's affordability posture as the need for more economically viable access to space solutions are needed in today's constrained economic environment. The problem of ascent trajectory optimization is not a new one. There are several programs that are widely used in industry that allows trajectory analysts to, based on detailed vehicle and insertion orbit parameters, determine the optimal ascent trajectory. Yet, little information is known about the launch vehicle early in the design phase - information that is required of many different disciplines in order to successfully optimize the ascent trajectory. Thus, the current paradigm of optimizing ascent trajectories involves generating point solutions for every change in a vehicle's design parameters. This is often a very tedious, manual, and time-consuming task for the analysts. Moreover, the trajectory design space is highly non-linear and multi

Ferroelectric materials for piezoelectric actuators by optimal design

International Nuclear Information System (INIS)

Jayachandran, K.P.; Guedes, J.M.; Rodrigues, H.C.

2011-01-01

Research highlights: → Microstructure optimization of ferroelectric materials by stochastic optimization. → Polycrystalline ferroelectrics possess better piezo actuation than single crystals. → Randomness of the grain orientations would enhance the overall piezoelectricity. - Abstract: Optimization methods provide a systematic means of designing heterogeneous materials with tailored properties and microstructures focussing on a specific objective. An optimization procedure incorporating a continuum modeling is used in this work to identify the ideal orientation distribution of ferroelectrics (FEs) for application in piezoelectric actuators. Piezoelectric actuation is dictated primarily by the piezoelectric strain coefficients d iμ . Crystallographic orientation is inextricably related to the piezoelectric properties of FEs. This suggests that piezoelectric properties can be tailored by a proper choice of the parameters which control the orientation distribution. Nevertheless, this choice is complicated and it is impossible to analyze all possible combinations of the distribution parameters or the angles themselves. Stochastic optimization combined with a generalized Monte Carlo scheme is used to optimize the objective functions, the effective piezoelectric coefficients d 31 and d 15 . The procedure is applied to heterogeneous, polycrystalline, FE ceramics which are essentially an aggregate of variously oriented grains (crystallites). Global piezoelectric properties are calculated using the homogenization method at each grain configuration chosen by the optimization algorithm. Optimal design variables and microstructure that would generate polycrystalline configurations that multiply the macroscopic piezoelectricity are identified.

Multidisciplinary Design, Analysis, and Optimization Tool Development Using a Genetic Algorithm

Science.gov (United States)

Pak, Chan-gi; Li, Wesley

2009-01-01

Multidisciplinary design, analysis, and optimization using a genetic algorithm is being developed at the National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) to automate analysis and design process by leveraging existing tools to enable true multidisciplinary optimization in the preliminary design stage of subsonic, transonic, supersonic, and hypersonic aircraft. This is a promising technology, but faces many challenges in large-scale, real-world application. This report describes current approaches, recent results, and challenges for multidisciplinary design, analysis, and optimization as demonstrated by experience with the Ikhana fire pod design.!

Slot Optimization Design of Induction Motor for Electric Vehicle

Science.gov (United States)

Shen, Yiming; Zhu, Changqing; Wang, Xiuhe

2018-01-01

Slot design of induction motor has a great influence on its performance. The RMxprt module based on magnetic circuit method can be used to analyze the influence of rotor slot type on motor characteristics and optimize slot parameters. In this paper, the authors take an induction motor of electric vehicle for a typical example. The first step of the design is to optimize the rotor slot by RMxprt, and then compare the main performance of the motor before and after the optimization through Ansoft Maxwell 2D. After that, the combination of optimum slot type and the optimum parameters are obtained. The results show that the power factor and the starting torque of the optimized motor have been improved significantly. Furthermore, the electric vehicle works at a better running status after the optimization.

Aircraft family design using enhanced collaborative optimization

Science.gov (United States)

Roth, Brian Douglas

Significant progress has been made toward the development of multidisciplinary design optimization (MDO) methods that are well-suited to practical large-scale design problems. However, opportunities exist for further progress. This thesis describes the development of enhanced collaborative optimization (ECO), a new decomposition-based MDO method. To support the development effort, the thesis offers a detailed comparison of two existing MDO methods: collaborative optimization (CO) and analytical target cascading (ATC). This aids in clarifying their function and capabilities, and it provides inspiration for the development of ECO. The ECO method offers several significant contributions. First, it enhances communication between disciplinary design teams while retaining the low-order coupling between them. Second, it provides disciplinary design teams with more authority over the design process. Third, it resolves several troubling computational inefficiencies that are associated with CO. As a result, ECO provides significant computational savings (relative to CO) for the test cases and practical design problems described in this thesis. New aircraft development projects seldom focus on a single set of mission requirements. Rather, a family of aircraft is designed, with each family member tailored to a different set of requirements. This thesis illustrates the application of decomposition-based MDO methods to aircraft family design. This represents a new application area, since MDO methods have traditionally been applied to multidisciplinary problems. ECO offers aircraft family design the same benefits that it affords to multidisciplinary design problems. Namely, it simplifies analysis integration, it provides a means to manage problem complexity, and it enables concurrent design of all family members. In support of aircraft family design, this thesis introduces a new wing structural model with sufficient fidelity to capture the tradeoffs associated with component

Design of large Francis turbine using optimal methods

Science.gov (United States)

Flores, E.; Bornard, L.; Tomas, L.; Liu, J.; Couston, M.

2012-11-01

Among a high number of Francis turbine references all over the world, covering the whole market range of heads, Alstom has especially been involved in the development and equipment of the largest power plants in the world : Three Gorges (China -32×767 MW - 61 to 113 m), Itaipu (Brazil- 20x750 MW - 98.7m to 127m) and Xiangjiaba (China - 8x812 MW - 82.5m to 113.6m - in erection). Many new projects are under study to equip new power plants with Francis turbines in order to answer an increasing demand of renewable energy. In this context, Alstom Hydro is carrying out many developments to answer those needs, especially for jumbo units such the planned 1GW type units in China. The turbine design for such units requires specific care by using the state of the art in computation methods and the latest technologies in model testing as well as the maximum feedback from operation of Jumbo plants already in operation. We present in this paper how a large Francis turbine can be designed using specific design methods, including the global and local optimization methods. The design of the spiral case, the tandem cascade profiles, the runner and the draft tube are designed with optimization loops involving a blade design tool, an automatic meshing software and a Navier-Stokes solver, piloted by a genetic algorithm. These automated optimization methods, presented in different papers over the last decade, are nowadays widely used, thanks to the growing computation capacity of the HPC clusters: the intensive use of such optimization methods at the turbine design stage allows to reach very high level of performances, while the hydraulic flow characteristics are carefully studied over the whole water passage to avoid any unexpected hydraulic phenomena.

Design of large Francis turbine using optimal methods

International Nuclear Information System (INIS)

Flores, E; Bornard, L; Tomas, L; Couston, M; Liu, J

2012-01-01

Among a high number of Francis turbine references all over the world, covering the whole market range of heads, Alstom has especially been involved in the development and equipment of the largest power plants in the world : Three Gorges (China −32×767 MW - 61 to 113 m), Itaipu (Brazil- 20x750 MW - 98.7m to 127m) and Xiangjiaba (China - 8x812 MW - 82.5m to 113.6m - in erection). Many new projects are under study to equip new power plants with Francis turbines in order to answer an increasing demand of renewable energy. In this context, Alstom Hydro is carrying out many developments to answer those needs, especially for jumbo units such the planned 1GW type units in China. The turbine design for such units requires specific care by using the state of the art in computation methods and the latest technologies in model testing as well as the maximum feedback from operation of Jumbo plants already in operation. We present in this paper how a large Francis turbine can be designed using specific design methods, including the global and local optimization methods. The design of the spiral case, the tandem cascade profiles, the runner and the draft tube are designed with optimization loops involving a blade design tool, an automatic meshing software and a Navier-Stokes solver, piloted by a genetic algorithm. These automated optimization methods, presented in different papers over the last decade, are nowadays widely used, thanks to the growing computation capacity of the HPC clusters: the intensive use of such optimization methods at the turbine design stage allows to reach very high level of performances, while the hydraulic flow characteristics are carefully studied over the whole water passage to avoid any unexpected hydraulic phenomena.

Optimizing an experimental design for an electromagnetic experiment

Science.gov (United States)

Roux, Estelle; Garcia, Xavier

2013-04-01

Most of geophysical studies focus on data acquisition and analysis, but another aspect which is gaining importance is the discussion on acquisition of suitable datasets. This can be done through the design of an optimal experiment. Optimizing an experimental design implies a compromise between maximizing the information we get about the target and reducing the cost of the experiment, considering a wide range of constraints (logistical, financial, experimental …). We are currently developing a method to design an optimal controlled-source electromagnetic (CSEM) experiment to detect a potential CO2 reservoir and monitor this reservoir during and after CO2 injection. Our statistical algorithm combines the use of linearized inverse theory (to evaluate the quality of one given design via the objective function) and stochastic optimization methods like genetic algorithm (to examine a wide range of possible surveys). The particularity of our method is that it uses a multi-objective genetic algorithm that searches for designs that fit several objective functions simultaneously. One main advantage of this kind of technique to design an experiment is that it does not require the acquisition of any data and can thus be easily conducted before any geophysical survey. Our new experimental design algorithm has been tested with a realistic one-dimensional resistivity model of the Earth in the region of study (northern Spain CO2 sequestration test site). We show that a small number of well distributed observations have the potential to resolve the target. This simple test also points out the importance of a well chosen objective function. Finally, in the context of CO2 sequestration that motivates this study, we might be interested in maximizing the information we get about the reservoir layer. In that case, we show how the combination of two different objective functions considerably improve its resolution.

Reliability-Based Optimal Design for Very Large Floating Structure

Institute of Scientific and Technical Information of China (English)

ZHANG Shu-hua(张淑华); FUJIKUBO Masahiko

2003-01-01

Costs and losses induced by possible future extreme environmental conditions and difficulties in repairing post-yielding damage strongly suggest the need for proper consideration in design rather than just life loss prevention. This can be addressed through the development of design methodology that balances the initial cost of the very large floating structure (VLFS) against the expected potential losses resulting from future extreme wave-induced structural damage. Here, the development of a methodology for determining optimal, cost-effective design will be presented and applied to a VLFS located in the Tokyo bay. Optimal design criteria are determined based on the total expected life-cycle cost and acceptable damage probability and curvature of the structure, and a set of sizes of the structure are obtained. The methodology and applications require expressions of the initial cost and the expected life-cycle damage cost as functions of the optimal design variables. This study includes the methodology, total life-cycle cost function, structural damage modeling, and reliability analysis.

Optimal control design for a solar greenhouse

NARCIS (Netherlands)

Ooteghem, van R.J.C.

2007-01-01

The research of this thesis was part of a larger project aiming at the design of a greenhouse and an associated climate control that achieves optimal crop production with sustainable instead of fossil energy. This so called solar greenhouse design extends a conventional greenhouse with an improved

Cost Optimal System Identification Experiment Design

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning

A structural system identification experiment design method is formulated in the light of decision theory, structural reliability theory and optimization theory. The experiment design is based on a preposterior analysis, well-known from the classical decision theory. I.e. the decisions concerning...... reflecting the cost of the experiment and the value of obtained additional information. An example concerning design of an experiment for parametric identification of a single degree of freedom structural system shows the applicability of the experiment design method....... the experiment design are not based on obtained experimental data. Instead the decisions are based on the expected experimental data assumed to be obtained from the measurements, estimated based on prior information and engineering judgement. The design method provides a system identification experiment design...

A design approach for integrating thermoelectric devices using topology optimization

International Nuclear Information System (INIS)

Soprani, S.; Haertel, J.H.K.; Lazarov, B.S.; Sigmund, O.; Engelbrecht, K.

2016-01-01

Highlights: • The integration of a thermoelectric (TE) cooler into a robotic tool is optimized. • Topology optimization is suggested as design tool for TE integrated systems. • A 3D optimization technique using temperature dependent TE properties is presented. • The sensitivity of the optimization process to the boundary conditions is studied. • A working prototype is constructed and compared to the model results. - Abstract: Efficient operation of thermoelectric devices strongly relies on the thermal integration into the energy conversion system in which they operate. Effective thermal integration reduces the temperature differences between the thermoelectric module and its thermal reservoirs, allowing the system to operate more efficiently. This work proposes and experimentally demonstrates a topology optimization approach as a design tool for efficient integration of thermoelectric modules into systems with specific design constraints. The approach allows thermal layout optimization of thermoelectric systems for different operating conditions and objective functions, such as temperature span, efficiency, and power recovery rate. As a specific application, the integration of a thermoelectric cooler into the electronics section of a downhole oil well intervention tool is investigated, with the objective of minimizing the temperature of the cooled electronics. Several challenges are addressed: ensuring effective heat transfer from the load, minimizing the thermal resistances within the integrated system, maximizing the thermal protection of the cooled zone, and enhancing the conduction of the rejected heat to the oil well. The design method incorporates temperature dependent properties of the thermoelectric device and other materials. The 3D topology optimization model developed in this work was used to design a thermoelectric system, complete with insulation and heat sink, that was produced and tested. Good agreement between experimental results and

Optimal design of NPC and Active-NPC transformerless PV inverters

DEFF Research Database (Denmark)

Saridakis, Stefanos; Koutroulis, Eftichios; Blaabjerg, Frede

2012-01-01

Targeting at a cost-effective deployment of grid-connected PhotoVoltaic (PV) systems, this paper presents a new methodology for the optimal design of transformerless PV inverters, which are based on the Neutral Point Clamped (NPC) and the Active-Neutral Point Clamped (ANPC) topologies. The design...... optimization results demonstrate that a different set of optimal values of the PV inverter switching frequency and output filter components are derived for the NPC and ANPC topologies, respectively, as well as for each of the PV inverter installation sites under study. The NPC and ANPC PV inverter structures......, which are derived using the proposed design optimization methodology exhibit lower Levelized Cost Of generated Electricity (LCOE) and manufacturing cost and they are simultaneously capable to inject more energy into the electric grid than the corresponding non-optimized PV inverters. Thus, the proposed...

Adaptive Clinical Trials: Advantages and Disadvantages of Various Adaptive Design Elements.

Science.gov (United States)

Korn, Edward L; Freidlin, Boris

2017-06-01

There is a wide range of adaptive elements of clinical trial design (some old and some new), with differing advantages and disadvantages. Classical interim monitoring, which adapts the design based on early evidence of superiority or futility of a treatment arm, has long been known to be extremely useful. A more recent application of interim monitoring is in the use of phase II/III designs, which can be very effective (especially in the setting of multiple experimental treatments and a reliable intermediate end point) but do have the cost of having to commit earlier to the phase III question than if separate phase II and phase III trials were performed. Outcome-adaptive randomization is an older technique that has recently regained attention; it increases trial complexity and duration without offering substantial benefits to the patients in the trial. The use of adaptive trials with biomarkers is new and has great potential for efficiently identifying patients who will be helped most by specific treatments. Master protocols in which trial arms and treatment questions are added to an ongoing trial can be especially efficient in the biomarker setting, where patients are screened for entry into different subtrials based on evolving knowledge about targeted therapies. A discussion of three recent adaptive clinical trials (BATTLE-2, I-SPY 2, and FOCUS4) highlights the issues. Published by Oxford University Press 2017. This work is written by US Government employees and is in the public domain in the US.

System-level design optimization of a hybrid tug

NARCIS (Netherlands)

Hofman, T.; Naaborg, M.; Sciberras, E.

2017-01-01

Designing a new vessel is a complex multi-objective design process. It involves knowledge from different fields, like naval architecture and mechanical engineering. Assessment of an optimal design for more complex topologies than a conventional Diesel powertrain becomes more difficult due to the

Microstrip Antenna Design for Femtocell Coverage Optimization

Directory of Open Access Journals (Sweden)

Afaz Uddin Ahmed

2014-01-01

Full Text Available A mircostrip antenna is designed for multielement antenna coverage optimization in femtocell network. Interference is the foremost concern for the cellular operator in vast commercial deployments of femtocell. Many techniques in physical, data link and network-layer are analysed and developed to settle down the interference issues. A multielement technique with self-configuration features is analyzed here for coverage optimization of femtocell. It also focuses on the execution of microstrip antenna for multielement configuration. The antenna is designed for LTE Band 7 by using standard FR4 dielectric substrate. The performance of the proposed antenna in the femtocell application is discussed along with results.

Global stability-based design optimization of truss structures using ...

Indian Academy of Sciences (India)

Furthermore, a pure pareto-ranking based multi-objective optimization model is employed for the design optimization of the truss structure with multiple objectives. The computational performance of the optimization model is increased by implementing an island model into its evolutionary search mechanism. The proposed ...

Application of Orthogonal Design to Optimize Extraction of ...

African Journals Online (AJOL)

Purpose: To optimize the extraction technology of polysaccharides from Cynomorium songaricum Rupr by ultrasonic-assisted extraction (UAE). Methods: Four parameters including ultrasonic power, ratio of raw material to water, extraction temperature, and extraction time were optimized by orthogonal design. The effects of ...

Optimizing Nuclear Reaction Analysis (NRA) using Bayesian Experimental Design

International Nuclear Information System (INIS)

Toussaint, Udo von; Schwarz-Selinger, Thomas; Gori, Silvio

2008-01-01

Nuclear Reaction Analysis with 3 He holds the promise to measure Deuterium depth profiles up to large depths. However, the extraction of the depth profile from the measured data is an ill-posed inversion problem. Here we demonstrate how Bayesian Experimental Design can be used to optimize the number of measurements as well as the measurement energies to maximize the information gain. Comparison of the inversion properties of the optimized design with standard settings reveals huge possible gains. Application of the posterior sampling method allows to optimize the experimental settings interactively during the measurement process.

Simulated annealing algorithm for reactor in-core design optimizations

International Nuclear Information System (INIS)

Zhong Wenfa; Zhou Quan; Zhong Zhaopeng

2001-01-01

A nuclear reactor must be optimized for in core fuel management to make full use of the fuel, to reduce the operation cost and to flatten the power distribution reasonably. The author presents a simulated annealing algorithm. The optimized objective function and the punishment function were provided for optimizing the reactor physics design. The punishment function was used to practice the simulated annealing algorithm. The practical design of the NHR-200 was calculated. The results show that the K eff can be increased by 2.5% and the power distribution can be flattened

A new decomposition-based computer-aided molecular/mixture design methodology for the design of optimal solvents and solvent mixtures

DEFF Research Database (Denmark)

Karunanithi, A.T.; Achenie, L.E.K.; Gani, Rafiqul

2005-01-01

This paper presents a novel computer-aided molecular/mixture design (CAMD) methodology for the design of optimal solvents and solvent mixtures. The molecular/mixture design problem is formulated as a mixed integer nonlinear programming (MINLP) model in which a performance objective is to be optim......This paper presents a novel computer-aided molecular/mixture design (CAMD) methodology for the design of optimal solvents and solvent mixtures. The molecular/mixture design problem is formulated as a mixed integer nonlinear programming (MINLP) model in which a performance objective...... is to be optimized subject to structural, property, and process constraints. The general molecular/mixture design problem is divided into two parts. For optimal single-compound design, the first part is solved. For mixture design, the single-compound design is first carried out to identify candidates...... and then the second part is solved to determine the optimal mixture. The decomposition of the CAMD MINLP model into relatively easy to solve subproblems is essentially a partitioning of the constraints from the original set. This approach is illustrated through two case studies. The first case study involves...

Optimal Design of Composite Structures Under Manufacturing Constraints

DEFF Research Database (Denmark)

Marmaras, Konstantinos

determination of the appropriate laminate thickness and the material choice in the structure. The optimal design problems that arise are stated as nonconvex mixed integer programming problems. We resort to different reformulation techniques to state the optimization problems as either linear or nonlinear convex....... The continuous relaxation of the mixed integer programming problems is being solved by an implementation of a primal–dual interior point method for nonlinear programming that updates the barrier parameter adaptively. The method is chosen for its excellent convergence properties and the ability of the method...... design phase results in structures with better structural performance reducing the need of manually post–processing the found designs....

A method of network topology optimization design considering application process characteristic

Science.gov (United States)

Wang, Chunlin; Huang, Ning; Bai, Yanan; Zhang, Shuo

2018-03-01

Communication networks are designed to meet the usage requirements of users for various network applications. The current studies of network topology optimization design mainly considered network traffic, which is the result of network application operation, but not a design element of communication networks. A network application is a procedure of the usage of services by users with some demanded performance requirements, and has obvious process characteristic. In this paper, we first propose a method to optimize the design of communication network topology considering the application process characteristic. Taking the minimum network delay as objective, and the cost of network design and network connective reliability as constraints, an optimization model of network topology design is formulated, and the optimal solution of network topology design is searched by Genetic Algorithm (GA). Furthermore, we investigate the influence of network topology parameter on network delay under the background of multiple process-oriented applications, which can guide the generation of initial population and then improve the efficiency of GA. Numerical simulations show the effectiveness and validity of our proposed method. Network topology optimization design considering applications can improve the reliability of applications, and provide guidance for network builders in the early stage of network design, which is of great significance in engineering practices.

The Family Spirit trial for American Indian teen mothers and their children: CBPR rationale, design, methods and baseline characteristics.

Science.gov (United States)

Mullany, Britta; Barlow, Allison; Neault, Nicole; Billy, Trudy; Jones, Tanya; Tortice, Iralene; Lorenzo, Sherilynn; Powers, Julia; Lake, Kristin; Reid, Raymond; Walkup, John

2012-10-01

The purpose of this paper is to describe the rationale, design, methods and baseline results of the Family Spirit trial. The goal of the trial is to evaluate the impact of the paraprofessional-delivered "Family Spirit" home-visiting intervention to reduce health and behavioral risks for American Indian teen mothers and their children. A community based participatory research (CBPR) process shaped the design of the current randomized controlled trial of the Family Spirit intervention. Between 2006 and 2008, 322 pregnant teens were randomized to receive the Family Spirit intervention plus Optimized Standard Care, or Optimized Standard Care alone. The Family Spirit intervention is a 43-session home-visiting curriculum administered by American Indian paraprofessionals to teen mothers from 28 weeks gestation until the baby's third birthday. A mixed methods assessment administered at nine intervals measures intervention impact on parental competence, mother's and children's social, emotional and behavioral risks for drug use, and maladaptive functioning. Participants are young (mean age = 18.1 years), predominantly primiparous, unmarried, and challenged by poverty, residential instability and low educational attainment. Lifetime and pregnancy drug use were ~2-4 times higher and ~5-6 times higher, respectively, than US All Races. Baseline characteristics were evenly distributed between groups, except for higher lifetime cigarette use and depressive symptoms among intervention mothers. If study aims are achieved, the public health field will have new evidence supporting multi-generational prevention of behavioral health disparities affecting young American Indian families and the utility of indigenous paraprofessional interventionists in under-resourced communities.

Structural Design Optimization On Thermally Induced Vibration

International Nuclear Information System (INIS)

Gu, Yuanxian; Chen, Biaosong; Zhang, Hongwu; Zhao, Guozhong

2002-01-01

The numerical method of design optimization for structural thermally induced vibration is originally studied in this paper and implemented in application software JIFEX. The direct and adjoint methods of sensitivity analysis for thermal induced vibration coupled with both linear and nonlinear transient heat conduction is firstly proposed. Based on the finite element method, the structural linear dynamics is treated simultaneously with coupled linear and nonlinear transient heat structural linear dynamics is treated simultaneously with coupled linear and nonlinear transient heat conduction. In the thermal analysis model, the nonlinear heat conduction considered is result from the radiation and temperature-dependent materials. The sensitivity analysis of transient linear and nonlinear heat conduction is performed with the precise time integration method. And then, the sensitivity analysis of structural transient dynamics is performed by the Newmark method. Both the direct method and the adjoint method are employed to derive the sensitivity equations of thermal vibration, and there are two adjoint vectors of structure and heat conduction respectively. The coupling effect of heat conduction on thermal vibration in the sensitivity analysis is particularly investigated. With coupling sensitivity analysis, the optimization model is constructed and solved by the sequential linear programming or sequential quadratic programming algorithm. The methods proposed have been implemented in the application software JIFEX of structural design optimization, and numerical examples are given to illustrate the methods and usage of structural design optimization on thermally induced vibration

The optimal design of UAV wing structure

Science.gov (United States)

Długosz, Adam; Klimek, Wiktor

2018-01-01

The paper presents an optimal design of UAV wing, made of composite materials. The aim of the optimization is to improve strength and stiffness together with reduction of the weight of the structure. Three different types of functionals, which depend on stress, stiffness and the total mass are defined. The paper presents an application of the in-house implementation of the evolutionary multi-objective algorithm in optimization of the UAV wing structure. Values of the functionals are calculated on the basis of results obtained from numerical simulations. Numerical FEM model, consisting of different composite materials is created. Adequacy of the numerical model is verified by results obtained from the experiment, performed on a tensile testing machine. Examples of multi-objective optimization by means of Pareto-optimal set of solutions are presented.

RO-75, Reverse Osmosis Plant Design Optimization and Cost Optimization

International Nuclear Information System (INIS)

Glueckstern, P.; Reed, S.A.; Wilson, J.V.

1999-01-01

1 - Description of problem or function: RO75 is a program for the optimization of the design and economics of one- or two-stage seawater reverse osmosis plants. 2 - Method of solution: RO75 evaluates the performance of the applied membrane module (productivity and salt rejection) at assumed operating conditions. These conditions include the site parameters - seawater salinity and temperature, the membrane module operating parameters - pressure and product recovery, and the membrane module predicted long-term performance parameters - lifetime and long flux decline. RO75 calculates the number of first and second stage (if applied) membrane modules needed to obtain the required product capacity and quality and evaluates the required pumping units and the power recovery turbine (if applied). 3 - Restrictions on the complexity of the problem: The program does not optimize or design the membrane properties and the internal structure and flow characteristics of the membrane modules; it assumes operating characteristics defined by the membrane manufacturers

Reliability-Based Design Optimization of Trusses with Linked-Discrete Design Variables using the Improved Firefly Algorithm

Directory of Open Access Journals (Sweden)

N. M. Okasha

2016-04-01

Full Text Available In this paper, an approach for conducting a Reliability-Based Design Optimization (RBDO of truss structures with linked-discrete design variables is proposed. The sections of the truss members are selected from the AISC standard tables and thus the design variables that represent the properties of each section are linked. Latin hypercube sampling is used in the evaluation of the structural reliability. The improved firefly algorithm is used for the optimization solution process. It was found that in order to use the improved firefly algorithm for efficiently solving problems of reliability-based design optimization with linked-discrete design variables; it needs to be modified as proposed in this paper to accelerate its convergence.

Electrostatic afocal-zoom lens design using computer optimization technique

Energy Technology Data Exchange (ETDEWEB)

Sise, Omer, E-mail: omersise@gmail.com

2014-12-15

Highlights: • We describe the detailed design of a five-element electrostatic afocal-zoom lens. • The simplex optimization is used to optimize lens voltages. • The method can be applied to multi-element electrostatic lenses. - Abstract: Electron optics is the key to the successful operation of electron collision experiments where well designed electrostatic lenses are needed to drive electron beam before and after the collision. In this work, the imaging properties and aberration analysis of an electrostatic afocal-zoom lens design were investigated using a computer optimization technique. We have found a whole new range of voltage combinations that has gone unnoticed until now. A full range of voltage ratios and spherical and chromatic aberration coefficients were systematically analyzed with a range of magnifications between 0.3 and 3.2. The grid-shadow evaluation was also employed to show the effect of spherical aberration. The technique is found to be useful for searching the optimal configuration in a multi-element lens system.

When ethics constrains clinical research: trial design of control arms in "greater than minimal risk" pediatric trials.

Science.gov (United States)

de Melo-Martín, Inmaculada; Sondhi, Dolan; Crystal, Ronald G

2011-09-01

For more than three decades clinical research in the United States has been explicitly guided by the idea that ethical considerations must be central to research design and practice. In spite of the centrality of this idea, attempting to balance the sometimes conflicting values of advancing scientific knowledge and protecting human subjects continues to pose challenges. Possible conflicts between the standards of scientific research and those of ethics are particularly salient in relation to trial design. Specifically, the choice of a control arm is an aspect of trial design in which ethical and scientific issues are deeply entwined. Although ethical quandaries related to the choice of control arms may arise when conducting any type of clinical trials, they are conspicuous in early phase gene transfer trials that involve highly novel approaches and surgical procedures and have children as the research subjects. Because of children's and their parents' vulnerabilities, in trials that investigate therapies for fatal, rare diseases affecting minors, the scientific and ethical concerns related to choosing appropriate controls are particularly significant. In this paper we use direct gene transfer to the central nervous system to treat late infantile neuronal ceroid lipofuscinosis to illustrate some of these ethical issues and explore possible solutions to real and apparent conflicts between scientific and ethical considerations.

Optimized emission in nanorod arrays through quasi-aperiodic inverse design.

Science.gov (United States)

Anderson, P Duke; Povinelli, Michelle L

2015-06-01

We investigate a new class of quasi-aperiodic nanorod structures for the enhancement of incoherent light emission. We identify one optimized structure using an inverse design algorithm and the finite-difference time-domain method. We carry out emission calculations on both the optimized structure as well as a simple periodic array. The optimized structure achieves nearly perfect light extraction while maintaining a high spontaneous emission rate. Overall, the optimized structure can achieve a 20%-42% increase in external quantum efficiency relative to a simple periodic design, depending on material quality.

Design optimization of transformerless grid-connected PV inverters including reliability

DEFF Research Database (Denmark)

Koutroulis, Eftichios; Blaabjerg, Frede

2012-01-01

Of the Electricity (LCOE) generated during the PV system lifetime period is minimized. The LCOE is calculated also considering the failure rates of the components, which affect the reliability performance and lifetime maintenance cost of the PV inverter. A design example is presented, demonstrating that compared...... to the non-optimized PV inverter structures, the PV inverters designed using the proposed optimization methodology exhibit lower total manufacturing and lifetime maintenance cost and inject more energy into the electric-grid and by that minimizing LCOE.......This paper presents a new methodology for optimal design of transformerless Photovoltaic (PV) inverters targeting a cost-effective deployment of grid-connected PV systems. The optimal values and types of the PV inverter components are calculated such that the PV inverter Levelized Cost...

Design Optimization of Transformerless Grid-Connected PV Inverters Including Reliability

DEFF Research Database (Denmark)

Koutroulis, Eftichios; Blaabjerg, Frede

2013-01-01

such that the PV inverter LCOE generated during the PV system lifetime period is minimized. The LCOE is also calculated considering the failure rates of the components, which affect the reliability performance and lifetime maintenance cost of the PV inverter. A design example is presented, demonstrating...... that compared to the nonoptimized PV inverter structures, the PV inverters designed using the proposed optimization methodology exhibit lower total manufacturing and lifetime maintenance cost and inject more energy into the electric-grid and by that minimizing LCOE.......This paper presents a new methodology for optimal design of transformerless photovoltaic (PV) inverters targeting a cost-effective deployment of grid-connected PV systems. The optimal switching frequency as well as the optimal values and types of the PV inverter components is calculated...

Ethical considerations of neuro-oncology trial design in the era of precision medicine.

Science.gov (United States)

Gupta, Saksham; Smith, Timothy R; Broekman, Marike L

2017-08-01

The field of oncology is currently undergoing a paradigm shift. Advances in the understanding of tumor biology and in tumor sequencing technology have contributed to the shift towards precision medicine, the therapeutic framework of targeting the individual oncogenic changes each tumor harbors. The success of precision medicine therapies, such as targeted kinase inhibitors and immunotherapies, in other cancers have motivated studies in brain cancers. The high specificity and cost of these therapies also encourage a shift in clinical trial design away from randomized control trials towards smaller, more exclusive early phase clinical trials. While these new trials advance the clinical application of increasingly precise and individualized therapies, their design brings ethical challenges . We review the pertinent ethical considerations for clinical trials of precision medicine in neuro-oncology and discuss methods to protect patients in this new era of trial design.

Basis and Statistical Design of the Passive HIV-1 Antibody Mediated Prevention (AMP) Test-of-Concept Efficacy Trials.

Science.gov (United States)

Gilbert, Peter B; Juraska, Michal; deCamp, Allan C; Karuna, Shelly; Edupuganti, Srilatha; Mgodi, Nyaradzo; Donnell, Deborah J; Bentley, Carter; Sista, Nirupama; Andrew, Philip; Isaacs, Abby; Huang, Yunda; Zhang, Lily; Capparelli, Edmund; Kochar, Nidhi; Wang, Jing; Eshleman, Susan H; Mayer, Kenneth H; Magaret, Craig A; Hural, John; Kublin, James G; Gray, Glenda; Montefiori, David C; Gomez, Margarita M; Burns, David N; McElrath, Julie; Ledgerwood, Julie; Graham, Barney S; Mascola, John R; Cohen, Myron; Corey, Lawrence

2017-01-01

Anti-HIV-1 broadly neutralizing antibodies (bnAbs) have been developed as potential agents for prevention of HIV-1 infection. The HIV Vaccine Trials Network and the HIV Prevention Trials Network are conducting the Antibody Mediated Prevention (AMP) trials to assess whether, and how, intravenous infusion of the anti-CD4 binding site bnAb, VRC01, prevents HIV-1 infection. These are the first test-of-concept studies to assess HIV-1 bnAb prevention efficacy in humans. The AMP trials are two parallel phase 2b HIV-1 prevention efficacy trials conducted in two cohorts: 2700 HIV-uninfected men and transgender persons who have sex with men in the United States, Peru, Brazil, and Switzerland; and 1500 HIV-uninfected sexually active women in seven countries in sub-Saharan Africa. Participants are randomized 1:1:1 to receive an intravenous infusion of 10 mg/kg VRC01, 30 mg/kg VRC01, or a control preparation every 8 weeks for a total of 10 infusions. Each trial is designed (1) to assess overall prevention efficacy (PE) pooled over the two VRC01 dose groups vs. control and (2) to assess VRC01 dose and laboratory markers as correlates of protection (CoPs) against overall and genotype- and phenotype-specific infection. Each AMP trial is designed to have 90% power to detect PE > 0% if PE is ≥ 60%. The AMP trials are also designed to identify VRC01 properties (i.e., concentration and effector functions) that correlate with protection and to provide insight into mechanistic CoPs. CoPs are assessed using data from breakthrough HIV-1 infections, including genetic sequences and sensitivities to VRC01-mediated neutralization and Fc effector functions. The AMP trials test whether VRC01 can prevent HIV-1 infection in two study populations. If affirmative, they will provide information for estimating the optimal dosage of VRC01 (or subsequent derivatives) and identify threshold levels of neutralization and Fc effector functions associated with high-level protection, setting a benchmark

High-Fidelity Multidisciplinary Design Optimization of Aircraft Configurations

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Martins, Joaquim R. R. A.; Kenway, Gaetan K. W.; Burdette, David; Jonsson, Eirikur; Kennedy, Graeme J.

2017-01-01

To evaluate new airframe technologies we need design tools based on high-fidelity models that consider multidisciplinary interactions early in the design process. The overarching goal of this NRA is to develop tools that enable high-fidelity multidisciplinary design optimization of aircraft configurations, and to apply these tools to the design of high aspect ratio flexible wings. We develop a geometry engine that is capable of quickly generating conventional and unconventional aircraft configurations including the internal structure. This geometry engine features adjoint derivative computation for efficient gradient-based optimization. We also added overset capability to a computational fluid dynamics solver, complete with an adjoint implementation and semiautomatic mesh generation. We also developed an approach to constraining buffet and started the development of an approach for constraining utter. On the applications side, we developed a new common high-fidelity model for aeroelastic studies of high aspect ratio wings. We performed optimal design trade-o s between fuel burn and aircraft weight for metal, conventional composite, and carbon nanotube composite wings. We also assessed a continuous morphing trailing edge technology applied to high aspect ratio wings. This research resulted in the publication of 26 manuscripts so far, and the developed methodologies were used in two other NRAs. 1

Configurable intelligent optimization algorithm design and practice in manufacturing

CERN Document Server

Tao, Fei; Laili, Yuanjun

2014-01-01

Presenting the concept and design and implementation of configurable intelligent optimization algorithms in manufacturing systems, this book provides a new configuration method to optimize manufacturing processes. It provides a comprehensive elaboration of basic intelligent optimization algorithms, and demonstrates how their improvement, hybridization and parallelization can be applied to manufacturing. Furthermore, various applications of these intelligent optimization algorithms are exemplified in detail, chapter by chapter. The intelligent optimization algorithm is not just a single algorit

Determination of the optimal sample size for a clinical trial accounting for the population size.

Science.gov (United States)

Stallard, Nigel; Miller, Frank; Day, Simon; Hee, Siew Wan; Madan, Jason; Zohar, Sarah; Posch, Martin

2017-07-01

The problem of choosing a sample size for a clinical trial is a very common one. In some settings, such as rare diseases or other small populations, the large sample sizes usually associated with the standard frequentist approach may be infeasible, suggesting that the sample size chosen should reflect the size of the population under consideration. Incorporation of the population size is possible in a decision-theoretic approach either explicitly by assuming that the population size is fixed and known, or implicitly through geometric discounting of the gain from future patients reflecting the expected population size. This paper develops such approaches. Building on previous work, an asymptotic expression is derived for the sample size for single and two-arm clinical trials in the general case of a clinical trial with a primary endpoint with a distribution of one parameter exponential family form that optimizes a utility function that quantifies the cost and gain per patient as a continuous function of this parameter. It is shown that as the size of the population, N, or expected size, N∗ in the case of geometric discounting, becomes large, the optimal trial size is O(N1/2) or O(N∗1/2). The sample size obtained from the asymptotic expression is also compared with the exact optimal sample size in examples with responses with Bernoulli and Poisson distributions, showing that the asymptotic approximations can also be reasonable in relatively small sample sizes. © 2016 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Particle Swarm Optimization for Outdoor Lighting Design

Directory of Open Access Journals (Sweden)

Ana Castillo-Martinez

2017-01-01

Full Text Available Outdoor lighting is an essential service for modern life. However, the high influence of this type of facility on energy consumption makes it necessary to take extra care in the design phase. Therefore, this manuscript describes an algorithm to help light designers to get, in an easy way, the best configuration parameters and to improve energy efficiency, while ensuring a minimum level of overall uniformity. To make this possible, we used a particle swarm optimization (PSO algorithm. These algorithms are well established, and are simple and effective to solve optimization problems. To take into account the most influential parameters on lighting and energy efficiency, 500 simulations were performed using DIALux software (4.10.0.2, DIAL, Ludenscheid, Germany. Next, the relation between these parameters was studied using to data mining software. Subsequently, we conducted two experiments for setting parameters that enabled the best configuration algorithm in order to improve efficiency in the proposed process optimization.

Nonlinear Shaping Architecture Designed with Using Evolutionary Structural Optimization Tools

Science.gov (United States)

Januszkiewicz, Krystyna; Banachowicz, Marta

2017-10-01

The paper explores the possibilities of using Structural Optimization Tools (ESO) digital tools in an integrated structural and architectural design in response to the current needs geared towards sustainability, combining ecological and economic efficiency. The first part of the paper defines the Evolutionary Structural Optimization tools, which were developed specifically for engineering purposes using finite element analysis as a framework. The development of ESO has led to several incarnations, which are all briefly discussed (Additive ESO, Bi-directional ESO, Extended ESO). The second part presents result of using these tools in structural and architectural design. Actual building projects which involve optimization as a part of the original design process will be presented (Crematorium in Kakamigahara Gifu, Japan, 2006 SANAA“s Learning Centre, EPFL in Lausanne, Switzerland 2008 among others). The conclusion emphasizes that the structural engineering and architectural design mean directing attention to the solutions which are used by Nature, designing works optimally shaped and forming their own environments. Architectural forms never constitute the optimum shape derived through a form-finding process driven only by structural optimization, but rather embody and integrate a multitude of parameters. It might be assumed that there is a similarity between these processes in nature and the presented design methods. Contemporary digital methods make the simulation of such processes possible, and thus enable us to refer back to the empirical methods of previous generations.

GENETIC ALGORITHM IN OPTIMIZATION DESIGN OF INTERIOR PERMANENT MAGNET SYNCHRONOUS MOTOR

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Phuong Le Ngo

2017-01-01

Full Text Available Classical method of designing electric motors help to achieve functional motor, but doesn’t ensure minimal cost in manufacturing and operating. Recently optimization is becoming an important part in modern electric motor design process. The objective of the optimization process is usually to minimize cost, energy loss, mass, or maximize torque and efficiency. Most of the requirements for electrical machine design are in contradiction to each other (reduction in volume or mass, improvement in efficiency etc.. Optimization in design permanent magnet synchronous motor (PMSM is a multi-objective optimization problem. There are two approaches for solving this problem, one of them is evolution algorithms, which gain a lot of attentions recently. For designing PMSM, evolution algorithms are more attractive approach. Genetic algorithm is one of the most common. This paper presents components and procedures of genetic algorithms, and its implementation on computer. In optimization process, analytical and finite element method are used together for better performance and precision. Result from optimization process is a set of solutions, from which engineer will choose one. This method was used to design a permanent magnet synchronous motor based on an asynchronous motor type АИР112МВ8.

Inverse design of dielectric materials by topology optimization

DEFF Research Database (Denmark)

Otomori, M.; Andkjær, Jacob Anders; Sigmund, Ole

2012-01-01

The capabilities and operation of electromagnetic devices can be dramatically enhanced if artificial materials that provide certain prescribed properties can be designed and fabricated. This paper presents a systematic methodology for the design of dielectric materials with prescribed electric...... permittivity. A gradient-based topology optimization method is used to find the distribution of dielectric material for the unit cell of a periodic microstructure composed of one or two dielectric materials. The optimization problem is formulated as a problem to minimize the square of the difference between...

An Expert System-Driven Method for Parametric Trajectory Optimization During Conceptual Design

Science.gov (United States)

Dees, Patrick D.; Zwack, Mathew R.; Steffens, Michael; Edwards, Stephen; Diaz, Manuel J.; Holt, James B.

2015-01-01

During the early phases of engineering design, the costs committed are high, costs incurred are low, and the design freedom is high. It is well documented that decisions made in these early design phases drive the entire design's life cycle cost. In a traditional paradigm, key design decisions are made when little is known about the design. As the design matures, design changes become more difficult in both cost and schedule to enact. The current capability-based paradigm, which has emerged because of the constrained economic environment, calls for the infusion of knowledge usually acquired during later design phases into earlier design phases, i.e. bringing knowledge acquired during preliminary and detailed design into pre-conceptual and conceptual design. An area of critical importance to launch vehicle design is the optimization of its ascent trajectory, as the optimal trajectory will be able to take full advantage of the launch vehicle's capability to deliver a maximum amount of payload into orbit. Hence, the optimal ascent trajectory plays an important role in the vehicle's affordability posture yet little of the information required to successfully optimize a trajectory is known early in the design phase. Thus, the current paradigm of optimizing ascent trajectories involves generating point solutions for every change in a vehicle's design parameters. This is often a very tedious, manual, and time-consuming task for the analysts. Moreover, the trajectory design space is highly non-linear and multi-modal due to the interaction of various constraints. When these obstacles are coupled with the Program to Optimize Simulated Trajectories (POST), an industry standard program to optimize ascent trajectories that is difficult to use, expert trajectory analysts are required to effectively optimize a vehicle's ascent trajectory. Over the course of this paper, the authors discuss a methodology developed at NASA Marshall's Advanced Concepts Office to address these issues

Design Optimization of Piles for Offshore Wind Turbine Jacket Foundations

DEFF Research Database (Denmark)

Sandal, Kasper; Zania, Varvara

Numerical methods can optimize the pile design. The aim of this study is to automatically design optimal piles for offshore wind turbine jacket foundations (Figure 1). Pile mass is minimized with constraints on axial and lateral capacity. Results indicate that accurate knowledge about soil...

Design of AC-DC Grid Connected Converter using Multi-Objective Optimization

Directory of Open Access Journals (Sweden)

Piasecki Szymon

2014-05-01

Full Text Available Power electronic circuits, in particular AC-DC converters are complex systems, many different parameters and objectives have to be taken into account during the design process. Implementation of Multi-Objective Optimization (MOO seems to be attractive idea, which used as designer supporting tool gives possibility for better analysis of the designed system. This paper presents a short introduction to the MOO applied in the field of power electronics. Short introduction to the subject is given in section I. Then, optimization process and its elements are briefly described in section II. Design procedure with proposed optimization parameters and performance indices for AC-DC Grid Connected Converter (GCC interfacing distributed systems is introduced in section III. Some preliminary optimization results, achieved on the basis of analytical and simulation study, are shown at each stage of designing process. Described optimization parameters and performance indices are part of developed global optimization method dedicated for ACDC GCC introduced in section IV. Described optimization method is under development and only short introduction and basic assumptions are presented. In section V laboratory prototype of high efficient and compact 14 kVA AC-DC converter is introduced. The converter is elaborated based on performed designing and optimization procedure with the use of silicon carbide (SiC power semiconductors. Finally, the paper is summarized and concluded in section VI. In presented work theoretical research are conducted in parallel with laboratory prototyping e.g. all theoretical ideas are verified in laboratory using modern DSP microcontrollers and prototypes of the ACDC GCC.

A Randomized Exchange Algorithm for Computing Optimal Approximate Designs of Experiments

KAUST Repository

Harman, Radoslav; Filová , Lenka; Richtarik, Peter

2018-01-01

We propose a class of subspace ascent methods for computing optimal approximate designs that covers both existing as well as new and more efficient algorithms. Within this class of methods, we construct a simple, randomized exchange algorithm (REX). Numerical comparisons suggest that the performance of REX is comparable or superior to the performance of state-of-the-art methods across a broad range of problem structures and sizes. We focus on the most commonly used criterion of D-optimality that also has applications beyond experimental design, such as the construction of the minimum volume ellipsoid containing a given set of data-points. For D-optimality, we prove that the proposed algorithm converges to the optimum. We also provide formulas for the optimal exchange of weights in the case of the criterion of A-optimality. These formulas enable one to use REX for computing A-optimal and I-optimal designs.

A Randomized Exchange Algorithm for Computing Optimal Approximate Designs of Experiments

KAUST Repository

Harman, Radoslav

2018-01-17

We propose a class of subspace ascent methods for computing optimal approximate designs that covers both existing as well as new and more efficient algorithms. Within this class of methods, we construct a simple, randomized exchange algorithm (REX). Numerical comparisons suggest that the performance of REX is comparable or superior to the performance of state-of-the-art methods across a broad range of problem structures and sizes. We focus on the most commonly used criterion of D-optimality that also has applications beyond experimental design, such as the construction of the minimum volume ellipsoid containing a given set of data-points. For D-optimality, we prove that the proposed algorithm converges to the optimum. We also provide formulas for the optimal exchange of weights in the case of the criterion of A-optimality. These formulas enable one to use REX for computing A-optimal and I-optimal designs.

Bamboo-inspired optimal design for functionally graded hollow cylinders.

Directory of Open Access Journals (Sweden)

Motohiro Sato

Full Text Available The optimal distribution of the reinforcing fibers for stiffening hollow cylindrical composites is explored using the linear elasticity theory. The spatial distribution of the vascular bundles in wild bamboo, a nature-designed functionally graded material, is the basis for the design. Our results suggest that wild bamboos maximize their flexural rigidity by optimally regulating the radial gradation of their vascular bundle distribution. This fact provides us with a plant-mimetic design principle that enables the realization of high-stiffness and lightweight cylindrical composites.

Implicit geometric representations for optimal design of gas turbine blades

International Nuclear Information System (INIS)

Mansour, T.; Ghaly, W.

2004-01-01

Shape optimization requires a proper geometric representation of the blade profile; the parameters of such a representation are usually taken as design variables in the optimization process. This implies that the model must possess three specific features: flexibility, efficiency, and accuracy. For the specific task of aerodynamic optimization for turbine blades, it is critical to have flexibility in both the global and local design spaces in order to obtain a successful optimization. This work is concerned with the development of two geometric representations of turbine blade profiles that are appropriate for aerodynamic optimization: the Modified Rapid Axial Turbine Design (MRATD) model where the blade is represented by five low-order curves that satisfy eleven designer parameters; this model is suitable for a global search of the design space. The second model is NURBS parameterization of the blade profile that can be used for a local refinement. The two models are presented and are assessed for flexibility and accuracy when representing several typical turbine blade profiles. The models will be further discussed in terms of curve smoothness and blade shape representation with a multi-NURBS curve versus one curve and its effect on the flow field, in particular the pressure distribution along the blade surfaces, will be elaborated. (author)

Placebo effect in clinical trial design for irritable bowel syndrome.

Science.gov (United States)

Shah, Eric; Pimentel, Mark

2014-04-30

Ongoing efforts to improve clinical trial design in irritable bowel syndrome have been hindered by high placebo response rates and ineffective outcome measures. We assessed established strategies to minimize placebo effect as well as the various ap-proaches to placebo effect which can affect trial design. These include genetic markers such as catechol-O-methyltransferase, opioidergic and dopaminergic neurobiologic theory, pre-cebo effect centered on expectancy theory, and side effect unblinding grounded on conditioning theory. We reviewed endpoints used in the study of IBS over the past decade including adequate relief and subjective global relief, emphasizing their weaknesses in fully evaluating the IBS condition, specifically their motility effects based on functional net value and relative benefit-harm based on dropouts due to adverse events. The focus of this review is to highlight ongoing efforts to improve clinical trial design which can lead to better outcomes in a real-world setting.

Importance of design optimization of gamma processing plants

International Nuclear Information System (INIS)

George, Jain Reji

2014-01-01

Radiation processing of food commodities using ionizing radiations is well established world wide. In India too, novel designs are coming up for food irradiation as well as for multiproduct irradiation. It has been observed that though the designs of the product movement systems are excelling, the actual purpose for which the designs are made are failing in some. In such situations it is difficult to achieve an effective dose delivery by controlling the process parameters or even by modifying the source activity distribution without compromising some other aspects like throughput. It is very essential to arrive at an optimization in all components such as radiation source geometry, source product geometry and protective barriers of an irradiator system. Optimization of the various parameters can be done by modeling and analysis of the design

Resilience-based optimal design of water distribution network

Science.gov (United States)

Suribabu, C. R.

2017-11-01

Optimal design of water distribution network is generally aimed to minimize the capital cost of the investments on tanks, pipes, pumps, and other appurtenances. Minimizing the cost of pipes is usually considered as a prime objective as its proportion in capital cost of the water distribution system project is very high. However, minimizing the capital cost of the pipeline alone may result in economical network configuration, but it may not be a promising solution in terms of resilience point of view. Resilience of the water distribution network has been considered as one of the popular surrogate measures to address ability of network to withstand failure scenarios. To improve the resiliency of the network, the pipe network optimization can be performed with two objectives, namely minimizing the capital cost as first objective and maximizing resilience measure of the configuration as secondary objective. In the present work, these two objectives are combined as single objective and optimization problem is solved by differential evolution technique. The paper illustrates the procedure for normalizing the objective functions having distinct metrics. Two of the existing resilience indices and power efficiency are considered for optimal design of water distribution network. The proposed normalized objective function is found to be efficient under weighted method of handling multi-objective water distribution design problem. The numerical results of the design indicate the importance of sizing pipe telescopically along shortest path of flow to have enhanced resiliency indices.

Solar Collector Design Optimization: A Hands-on Project Case Study

Science.gov (United States)

Birnie, Dunbar P., III; Kaz, David M.; Berman, Elena A.

2012-01-01

A solar power collector optimization design project has been developed for use in undergraduate classrooms and/or laboratories. The design optimization depends on understanding the current-voltage characteristics of the starting photovoltaic cells as well as how the cell's electrical response changes with increased light illumination. Students…

Evaluating Varied Label Designs for Use with Medical Devices: Optimized Labels Outperform Existing Labels in the Correct Selection of Devices and Time to Select.

Directory of Open Access Journals (Sweden)

Laura Bix

Full Text Available Effective standardization of medical device labels requires objective study of varied designs. Insufficient empirical evidence exists regarding how practitioners utilize and view labeling.Measure the effect of graphic elements (boxing information, grouping information, symbol use and color-coding to optimize a label for comparison with those typical of commercial medical devices.Participants viewed 54 trials on a computer screen. Trials were comprised of two labels that were identical with regard to graphics, but differed in one aspect of information (e.g., one had latex, the other did not. Participants were instructed to select the label along a given criteria (e.g., latex containing as quickly as possible. Dependent variables were binary (correct selection and continuous (time to correct selection.Eighty-nine healthcare professionals were recruited at Association of Surgical Technologists (AST conferences, and using a targeted e-mail of AST members.Symbol presence, color coding and grouping critical pieces of information all significantly improved selection rates and sped time to correct selection (α = 0.05. Conversely, when critical information was graphically boxed, probability of correct selection and time to selection were impaired (α = 0.05. Subsequently, responses from trials containing optimal treatments (color coded, critical information grouped with symbols were compared to two labels created based on a review of those commercially available. Optimal labels yielded a significant positive benefit regarding the probability of correct choice ((P<0.0001 LSM; UCL, LCL: 97.3%; 98.4%, 95.5%, as compared to the two labels we created based on commercial designs (92.0%; 94.7%, 87.9% and 89.8%; 93.0%, 85.3% and time to selection.Our study provides data regarding design factors, namely: color coding, symbol use and grouping of critical information that can be used to significantly enhance the performance of medical device labels.

Optimizing delivery of a behavioral pain intervention in cancer patients using a sequential multiple assignment randomized trial SMART.

Science.gov (United States)

Kelleher, Sarah A; Dorfman, Caroline S; Plumb Vilardaga, Jen C; Majestic, Catherine; Winger, Joseph; Gandhi, Vicky; Nunez, Christine; Van Denburg, Alyssa; Shelby, Rebecca A; Reed, Shelby D; Murphy, Susan; Davidian, Marie; Laber, Eric B; Kimmick, Gretchen G; Westbrook, Kelly W; Abernethy, Amy P; Somers, Tamara J

2017-06-01

Pain is common in cancer patients and results in lower quality of life, depression, poor physical functioning, financial difficulty, and decreased survival time. Behavioral pain interventions are effective and nonpharmacologic. Traditional randomized controlled trials (RCT) test interventions of fixed time and dose, which poorly represent successive treatment decisions in clinical practice. We utilize a novel approach to conduct a RCT, the sequential multiple assignment randomized trial (SMART) design, to provide comparative evidence of: 1) response to differing initial doses of a pain coping skills training (PCST) intervention and 2) intervention dose sequences adjusted based on patient response. We also examine: 3) participant characteristics moderating intervention responses and 4) cost-effectiveness and practicality. Breast cancer patients (N=327) having pain (ratings≥5) are recruited and randomly assigned to: 1) PCST-Full or 2) PCST-Brief. PCST-Full consists of 5 PCST sessions. PCST-Brief consists of one 60-min PCST session. Five weeks post-randomization, participants re-rate their pain and are re-randomized, based on intervention response, to receive additional PCST sessions, maintenance calls, or no further intervention. Participants complete measures of pain intensity, interference and catastrophizing. Novel RCT designs may provide information that can be used to optimize behavioral pain interventions to be adaptive, better meet patients' needs, reduce barriers, and match with clinical practice. This is one of the first trials to use a novel design to evaluate symptom management in cancer patients and in chronic illness; if successful, it could serve as a model for future work with a wide range of chronic illnesses. Copyright © 2016. Published by Elsevier Inc.

A General Multidisciplinary Turbomachinery Design Optimization system Applied to a Transonic Fan

Science.gov (United States)

Nemnem, Ahmed Mohamed Farid

The blade geometry design process is integral to the development and advancement of compressors and turbines in gas generators or aeroengines. A new airfoil section design capability has been added to an open source parametric 3D blade design tool. Curvature of the meanline is controlled using B-splines to create the airfoils. The curvature is analytically integrated to derive the angles and the meanline is obtained by integrating the angles. A smooth thickness distribution is then added to the airfoil to guarantee a smooth shape while maintaining a prescribed thickness distribution. A leading edge B-spline definition has also been implemented to achieve customized airfoil leading edges which guarantees smoothness with parametric eccentricity and droop. An automated turbomachinery design and optimization system has been created. An existing splittered transonic fan is used as a test and reference case. This design was more general than a conventional design to have access to the other design methodology. The whole mechanical and aerodynamic design loops are automated for the optimization process. The flow path and the geometrical properties of the rotor are initially created using the axi-symmetric design and analysis code (T-AXI). The main and splitter blades are parametrically designed with the created geometry builder (3DBGB) using the new added features (curvature technique). The solid model creation of the rotor sector with a periodic boundaries combining the main blade and splitter is done using MATLAB code directly connected to SolidWorks including the hub, fillets and tip clearance. A mechanical optimization is performed with DAKOTA (developed by DOE) to reduce the mass of the blades while keeping maximum stress as a constraint with a safety factor. A Genetic algorithm followed by Numerical Gradient optimization strategies are used in the mechanical optimization. The splittered transonic fan blades mass is reduced by 2.6% while constraining the maximum

Stiffness design of geometrically nonlinear structures using topology optimization

DEFF Research Database (Denmark)

Buhl, Thomas; Pedersen, Claus B. Wittendorf; Sigmund, Ole

2000-01-01

of the objective functions are found with the adjoint method and the optimization problem is solved using the Method of Moving Asymptotes. A filtering scheme is used to obtain checkerboard-free and mesh-independent designs and a continuation approach improves convergence to efficient designs. Different objective......The paper deals with topology optimization of structures undergoing large deformations. The geometrically nonlinear behaviour of the structures are modelled using a total Lagrangian finite element formulation and the equilibrium is found using a Newton-Raphson iterative scheme. The sensitivities...... functions are tested. Minimizing compliance for a fixed load results in degenerated topologies which are very inefficient for smaller or larger loads. The problem of obtaining degenerated "optimal" topologies which only can support the design load is even more pronounced than for structures with linear...

Design Optimization of a Centrifugal Fan with Splitter Blades

Science.gov (United States)

Heo, Man-Woong; Kim, Jin-Hyuk; Kim, Kwang-Yong

2015-05-01

Multi-objective optimization of a centrifugal fan with additionally installed splitter blades was performed to simultaneously maximize the efficiency and pressure rise using three-dimensional Reynolds-averaged Navier-Stokes equations and hybrid multi-objective evolutionary algorithm. Two design variables defining the location of splitter, and the height ratio between inlet and outlet of impeller were selected for the optimization. In addition, the aerodynamic characteristics of the centrifugal fan were investigated with the variation of design variables in the design space. Latin hypercube sampling was used to select the training points, and response surface approximation models were constructed as surrogate models of the objective functions. With the optimization, both the efficiency and pressure rise of the centrifugal fan with splitter blades were improved considerably compared to the reference model.

Optimal Halbach permanent magnet designs for maximally pulling and pushing nanoparticles

Energy Technology Data Exchange (ETDEWEB)

Sarwar, A., E-mail: azeem@umd.edu [Fischell Department of Bioengineering, College Park, MD (United States); University of Maryland at College Park (United States); Nemirovski, A. [H. Milton Stewart School of Industrial and Systems Engineering (ISyE), Georgia Institute of Technology (United States); Shapiro, B. [Fischell Department of Bioengineering, College Park, MD (United States); Institute for Systems Research (United States); University of Maryland at College Park (United States)

2012-03-15

Optimization methods are presented to design Halbach arrays to maximize the forces applied on magnetic nanoparticles at deep tissue locations. In magnetic drug targeting, where magnets are used to focus therapeutic nanoparticles to disease locations, the sharp fall off of magnetic fields and forces with distances from magnets has limited the depth of targeting. Creating stronger forces at a depth by optimally designed Halbach arrays would allow treatment of a wider class of patients, e.g. patients with deeper tumors. The presented optimization methods are based on semi-definite quadratic programming, yield provably globally optimal Halbach designs in 2 and 3-dimensions, for maximal pull or push magnetic forces (stronger pull forces can collect nanoparticles against blood forces in deeper vessels; push forces can be used to inject particles into precise locations, e.g. into the inner ear). These Halbach designs, here tested in simulations of Maxwell's equations, significantly outperform benchmark magnets of the same size and strength. For example, a 3-dimensional 36 element 2000 cm{sup 3} volume optimal Halbach design yields a 5 Multiplication-Sign greater force at a 10 cm depth compared to a uniformly magnetized magnet of the same size and strength. The designed arrays should be feasible to construct, as they have a similar strength ({<=}1 T), size ({<=}2000 cm{sup 3}), and number of elements ({<=}36) as previously demonstrated arrays, and retain good performance for reasonable manufacturing errors (element magnetization direction errors {<=}5 Degree-Sign), thus yielding practical designs to improve magnetic drug targeting treatment depths. - Highlights: Black-Right-Pointing-Pointer Optimization methods presented to design Halbach arrays for drug targeting. Black-Right-Pointing-Pointer The goal is to maximize forces on magnetic nanoparticles at deep tissue locations. Black-Right-Pointing-Pointer The presented methods yield provably globally optimal Halbach

Optimal Halbach permanent magnet designs for maximally pulling and pushing nanoparticles

International Nuclear Information System (INIS)