scholarly journals Robust Optimal Design of Beams Subject to Uncertain Loads

2009 ◽  
Vol 2009 ◽  
pp. 1-17 ◽  
Author(s):  
Ismail Kucuk ◽  
Sarp Adali ◽  
Ibrahim Sadek
Keyword(s):  
Optimal Design ◽  
Nonlinear Differential Equations ◽  
A Priori ◽  
Optimal Designs ◽  
Transverse Load ◽  
Cross Sectional ◽  
Worst Case ◽  
Operational Conditions ◽  
Robust Optimal Design ◽  
Optimal Area

Optimality conditions are derived for the robust optimal design of beams subject to a combination of uncertain and deterministic transverse and boundary loads using a variational min-max approach. The potential energy of the beam is maximized to compute the worst case loading and minimized to determine the optimal cross-sectional shape which results in coupled nonlinear differential equations for the unknown functions except for the case of a variable width beam. The uncertain component of the transverse load acting on the beam is not known a priori resulting in load uncertainty subject only to an norm constraint. Similarly the optimal area function is subject to a volume constraint leading to an isoperimetric variational problem. The min-max approach leads to robust optimal designs which are not susceptible to unexpected load variations as it occurs under operational conditions. The solution methodology is illustrated for the variable width beam by obtaining analytical results for several cases. The efficiency of the optimal designs is computed with respect to a uniform beam under worst case loading taking the maximum deflection as the quantity for comparison. It is observed that the optimal shapes are more than 70% efficient for the examples given in this study.

Robust Optimal Design for Worst-Case Tolerances

1994 ◽  
Vol 116 (4) ◽  
pp. 1019-1025 ◽  
Author(s):  
G. Emch ◽  
A. Parkinson
Keyword(s):  
Nonlinear Programming ◽  
Optimal Design ◽  
Worst Case ◽  
New Approach ◽  
Robust Designs ◽  
Design Variables ◽  
Robust Optimal Design ◽  
Programming Techniques ◽  
Engineering Models ◽  
Analytical Tools

Engineering models can and should be used to understand the effects of variability on a design. When variability is ignored, brittle designs can result that will not function properly or that will fail in service. By contrast, robust designs function properly even when subjected to off-nominal conditions. There is a need for better analytical tools to help engineers develop robust designs. In this paper we present a new approach for developing designs that are robust to variability induced by worst-case tolerances. An advantage of this approach is that tolerances may be placed on any or all model inputs, whether design variables or parameters. The method adapts nonlinear programming techniques in order to determine how a design should be modified to account for variability. We tested the method under relatively severe conditions on 13 problems, with excellent results. Using this approach, a designer can account for the effects of worst-case tolerances, making it possible to build robustness into an engineering design.

A Preference-Based Robust Design Metric

1998 ◽  
Author(s):  
Harikumar V. Iyer ◽  
Sundar Krishnamurty
Keyword(s):  
Decision Making ◽  
Optimal Design ◽  
Design Method ◽  
A Priori ◽  
Design Procedure ◽  
Design Criterion ◽  
Design Metrics ◽  
Overall Design ◽  
Space Reduction ◽  
Robust Optimal Design

Abstract Robust optimal design can be studied as a problem in decision-making requiring tradeoffs between mean and variance attributes. In this context, this paper views Taguchi’s philosophy based design metrics using signal-to-noise (SN) ratios as empirical applications of decision-making under uncertainty with a priori sets of attribute tradeoff values. Alternatively, this paper presents a more rigorous preference-based design metric using concepts from utility theory to accurately capture designer’s intent and preferences. The use of this design metric as the robust optimal design criterion in a modified TRED (Tradeoffs in Robust Engineering Design) method with an innovative response-surface based iterative design space reduction strategy is presented. The effectiveness of the overall design procedure and the performance of the preference-based design metric are tested with the aid of demonstrative case studies and the results are discussed.

Robust optimal design of a neutral valve for hydrostatic transmissions using Grey relational analysis

2016 ◽  
Vol 231 (18) ◽  
pp. 3414-3428
Author(s):  
Suchul Kim ◽  
Jaeseung Kim ◽  
Jinwoong Lee ◽  
Sungbo Shim ◽  
Kyeonguk Kim
Keyword(s):  
Optimal Design ◽  
Grey Relational Analysis ◽  
Design Parameters ◽  
Operational Conditions ◽  
Relational Analysis ◽  
Robust Optimal Design ◽  
Pressure Impact ◽  
Hydrostatic Transmissions ◽  
Grey Relational ◽  
Neutral Angle

Problems of pressure impact and improper neutral angle of a neutral valve for hydrostatic transmissions were solved using Taguchi method for robust optimal design with aids of Grey relational analysis and computer simulation. An ITI-Simulation X-based model of a hydrostatic transmission with the neutral valve was developed and used to simulate the pressure impact and extended neutral angle during the pressure modulation when the swash plate angled from neutral to forth or back. The simulation results were converted to the Grey relational coefficients for 108 combinations of 27 design and four operational conditions. The Grey relational grades were also calculated for seven design parameters and each of the design conditions as the performance index. Through three times repeated robust optimal design process, the design parameters reached to the optimal which satisfied the performance goals of the neutral valve set to smaller the better for the pressure impact and nominal the best for the extended neutral valve.

A General Approach for Robust Optimal Design

1993 ◽  
Vol 115 (1) ◽  
pp. 74-80 ◽  
Author(s):  
A. Parkinson ◽  
C. Sorensen ◽  
N. Pourhassan
Keyword(s):  
Statistical Analysis ◽  
Optimal Design ◽  
Design Optimization ◽  
Design Problem ◽  
Optimization Process ◽  
Worst Case ◽  
Rigorous Approach ◽  
Design Variables ◽  
Robust Optimal Design ◽  
And Control

This paper describes a general, rigorous approach for robust optimal design. The method allows a designer to explicitly consider and control, as an integrated part of the optimization process, the effects of variability in design variables and parameters on a design. Variability is defined in terms of tolerances which bracket the variation of fluctuating quantities. A designer can apply tolerances to any model input and can analyze how the tolerances affect the design using either a worst case or statistical analysis. As part of design optimization, the designer can apply the method to find an optimum that will remain feasible when subject to variation, and/or the designer can minimize or constrain the effects of tolerances as one of the objectives or constraints of the design problem.

Q-optimal experimental designs and close to them experimental designs for polynomial regression on the interval

2020 ◽  
Vol 86 (5) ◽  
pp. 65-72
Author(s):  
Yu. D. Grigoriev
Keyword(s):  
Optimal Design ◽  
Polynomial Regression ◽  
Direct Consequence ◽  
Experimental Designs ◽  
Optimal Designs ◽  
Software Systems ◽  
General Character ◽  
Support Points ◽  
Optimal Weights ◽  
Universal Expression

The problem of constructing Q-optimal experimental designs for polynomial regression on the interval [–1, 1] is considered. It is shown that well-known Malyutov – Fedorov designs using D-optimal designs (so-called Legendre spectrum) are other than Q-optimal designs. This statement is a direct consequence of Shabados remark which disproved the Erdős hypothesis that the spectrum (support points) of saturated D-optimal designs for polynomial regression on a segment appeared to be support points of saturated Q-optimal designs. We present a saturated exact Q-optimal design for polynomial regression with s = 3 which proves the Shabados notion and then extend this statement to approximate designs. It is shown that when s = 3, 4 the Malyutov – Fedorov theorem on approximate Q-optimal design is also incorrect, though it still stands for s = 1, 2. The Malyutov – Fedorov designs with Legendre spectrum are considered from the standpoint of their proximity to Q-optimal designs. Case studies revealed that they are close enough for small degrees s of polynomial regression. A universal expression for Q-optimal distribution of the weights pi for support points xi for an arbitrary spectrum is derived. The expression is used to tabulate the distribution of weights for Malyutov – Fedorov designs at s = 3, ..., 6. The general character of the obtained expression is noted for Q-optimal weights with A-optimal weight distribution (Pukelsheim distribution) for the same problem statement. In conclusion a brief recommendation on the numerical construction of Q-optimal designs is given. It is noted that in this case in addition to conventional numerical methods some software systems of symbolic computations using methods of resultants and elimination theory can be successfully applied. The examples of Q-optimal designs considered in the paper are constructed using precisely these methods.

scholarly journals Stillbirth outcome capture and classification in population-based surveys: EN-INDEPTH study

2021 ◽  
Vol 19 (S1) ◽  
Author(s):  
Hannah Blencowe ◽  
◽  
Matteo Bottecchia ◽  
Doris Kwesiga ◽  
Joseph Akuze ◽  
...  
Keyword(s):  
Gestational Age ◽  
A Priori ◽  
Healthcare Providers ◽  
Population Based ◽  
Reproductive Age ◽  
Group Discussions ◽  
Cross Sectional ◽  
Vital Status ◽  
Neonatal Deaths ◽  
Adverse Pregnancy

Abstract Background Household surveys remain important sources of stillbirth data, but omission and misclassification are common. Classifying adverse pregnancy outcomes as stillbirths requires accurate reporting of vital status at birth and gestational age or birthweight for every pregnancy. Further categorisation, e.g. by sex, or timing (intrapartum/antepartum) improves data to understand and prevent stillbirth. Methods We undertook a cross-sectional population-based survey of women of reproductive age in five health and demographic surveillance system sites in Bangladesh, Ethiopia, Ghana, Guinea-Bissau and Uganda (2017–2018). All women answered a full birth history with pregnancy loss questions (FBH+) or a full pregnancy history (FPH). A sub-sample across both groups were asked additional stillbirth questions. Questions were evaluated using descriptive measures. Using an interpretative paradigm and phenomenology methodology, focus group discussions with women exploring barriers to reporting birthweight for stillbirths were conducted. Thematic analysis was guided by an a priori codebook. Results Overall 69,176 women reported 98,483 livebirths (FBH+) and 102,873 pregnancies (FPH). Additional questions were asked for 1453 stillbirths, 1528 neonatal deaths and 12,620 surviving children born in the 5 years prior to the survey. Completeness was high (> 99%) for existing FBH+/FPH questions on signs of life at birth and gestational age (months). Discordant responses in signs of life at birth between different questions were common; nearly one-quarter classified as stillbirths on FBH+/FPH were reported born alive on additional questions. Availability of information on gestational age (weeks) (58.1%) and birthweight (13.2%) was low amongst stillbirths, and heaping was common. Most women (93.9%) were able to report the sex of their stillborn baby. Response completeness for stillbirth timing (18.3–95.1%) and estimated proportion intrapartum (15.6–90.0%) varied by question and site. Congenital malformations were reported in 3.1% stillbirths. Perceived value in weighing a stillborn baby varied and barriers to weighing at birth a nd knowing birthweight were common. Conclusions Improving stillbirth data in surveys will require investment in improving the measurement of vital status, gestational age and birthweight by healthcare providers, communication of these with women, and overcoming reporting barriers. Given the large burden and effect on families, improved data must be made available to end preventable stillbirths.

scholarly journals Methodological quality of systematic reviews on treatments for depression: a cross-sectional study

2017 ◽  
Vol 27 (6) ◽  
pp. 619-627 ◽  
Author(s):  
V. C. H. Chung ◽  
X. Y. Wu ◽  
Y. Feng ◽  
R. S. T. Ho ◽  
S. Y. S. Wong ◽  
...  
Keyword(s):  
Systematic Reviews ◽  
Methodological Quality ◽  
A Priori ◽  
Cross Sectional Study ◽  
Risk Of Bias ◽  
Sectional Study ◽  
Pharmacological Treatments ◽  
Cross Sectional ◽  
Depression Treatments

Aims.Depression is one of the most common mental disorders and identifying effective treatment strategies is crucial for the control of depression. Well-conducted systematic reviews (SRs) and meta-analyses can provide the best evidence for supporting treatment decision-making. Nevertheless, the trustworthiness of conclusions can be limited by lack of methodological rigour. This study aims to assess the methodological quality of a representative sample of SRs on depression treatments.Methods.A cross-sectional study on the bibliographical and methodological characteristics of SRs published on depression treatments trials was conducted. Two electronic databases (the Cochrane Database of Systematic Reviews and the Database of Abstracts of Reviews of Effects) were searched for potential SRs. SRs with at least one meta-analysis on the effects of depression treatments were considered eligible. The methodological quality of included SRs was assessed using the validated AMSTAR (Assessing the Methodological Quality of Systematic Reviews) tool. The associations between bibliographical characteristics and scoring on AMSTAR items were analysed using logistic regression analysis.Results.A total of 358 SRs were included and appraised. Over half of included SRs (n = 195) focused on non-pharmacological treatments and harms were reported in 45.5% (n = 163) of all studies. Studies varied in methods and reporting practices: only 112 (31.3%) took the risk of bias among primary studies into account when formulating conclusions; 245 (68.4%) did not fully declare conflict of interests; 93 (26.0%) reported an ‘a priori’ design and 104 (29.1%) provided lists of both included and excluded studies. Results from regression analyses showed: more recent publications were more likely to report ‘a priori’ designs [adjusted odds ratio (AOR) 1.31, 95% confidence interval (CI) 1.09–1.57], to describe study characteristics fully (AOR 1.16, 95% CI 1.06–1.28), and to assess presence of publication bias (AOR 1.13, 95% CI 1.06–1.19), but were less likely to list both included and excluded studies (AOR 0.86, 95% CI 0.81–0.92). SRs published in journals with higher impact factor (AOR 1.14, 95% CI 1.04–1.25), completed by more review authors (AOR 1.12, 95% CI 1.01–1.24) and SRs on non-pharmacological treatments (AOR 1.62, 95% CI 1.01–2.59) were associated with better performance in publication bias assessment.Conclusion.The methodological quality of included SRs is disappointing. Future SRs should strive to improve rigour by considering of risk of bias when formulating conclusions, reporting conflict of interests and authors should explicitly describe harms. SR authors should also use appropriate methods to combine the results, prevent language and publication biases, and ensure timely updates.

28 Assessment of Pain and Provision of Non-Pharmacologic Analgesia to Children by Prehospital Providers in Southwestern Ontario: A Cross-Sectional Study

2021 ◽  
Vol 26 (Supplement_1) ◽  
pp. e21-e21
Author(s):  
Karina Burke ◽  
Branka Vujcic ◽  
Jonathan Hamilton ◽  
Charlotte Mace ◽  
John Teefy ◽  
...  
Keyword(s):  
Primary Outcome ◽  
Rating Scale ◽  
A Priori ◽  
Numeric Rating Scale ◽  
Cross Sectional Study ◽  
Subject Area ◽  
Stepwise Logistic Regression ◽  
Tertiary Referral Centre ◽  
Cross Sectional ◽  
Pain Scores

Abstract Primary Subject area Emergency Medicine - Paediatric Background There is abundant evidence that provision of pharmacologic analgesia by prehospital providers to children is suboptimal. Most paediatric calls are performed by primary care paramedics (PCPs) who are unable to administer pharmacologic analgesia to children but can administer non-pharmacologic therapies. Objectives Our objective was to describe the provision of non-pharmacologic analgesia to children by prehospital providers. Design/Methods We reviewed all ambulance call reports (ACRs) of children 0-17 years with acutely painful conditions (headache, abdominal pain, injury, head/ears/eyes/nose/throat pain, and back pain) who were transported to a paediatric tertiary referral centre serving a catchment of > 1 million from 2017-2019. Data collection was recorded by two blinded assessors using a study-specific Excel™ sheet. The primary outcome was the proportion of children offered non-pharmacologic analgesia. We performed a stepwise logistic regression on the primary outcome using covariates defined a priori: age, sex, visible deformity, type of crew, complaint, pain score, call time, and prior analgesia. Results All 11,084 ACRs from January 1, 2017 to December 31, 2019 were reviewed. The sample included 5887/11084 (53.1%) males, ranging from 1 month to 17 years, with a mean (SD) age of 10.5 (5.6) years. Calls involved mainly PCPs [8576/11084 (77.4%)]. Non-trauma-related musculoskeletal injuries were most common, comprising 2743/11,084 (24.7%) of calls. Pain scores were documented in 6947/11084 (62.7%) of calls. The verbal numeric rating scale (0-10) was used in 5022/6947 (72.3%) of calls, with a mean (SD) score of 5.2 (3.2). Non-pharmacologic analgesia was provided in 2926/11084 (26.4%) of calls, most commonly splint (1115/2926, 38.1%) and ice (931/2926, 31.8%). Pharmacologic analgesia was provided in 458/11084 (4.1%) of calls. In the multivariate model, mild (OR: 3.2; 95% CI 2.3-4.4; p < 0 .001) and moderate pain (OR: 1.7; 95% CI 1.3-2.2) (versus no pain) were significant predictors of non-pharmacologic analgesia, whereas visible deformity (OR: 0.5; 95% CI 0.3-0.6; p < 0 .001) was a significant negative predictor. Conclusion The provision of non-pharmacologic analgesia to children in Southwestern Ontario by prehospital providers is suboptimal, despite moderate to severe pain. There is a clear need for education surrounding approaches to non-pharmacologic analgesia in children among prehospital providers.

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