Optimization Model For Design Research Articles

Hydrological modeling and analysis for optimal RCC dam design and construction

Hydrological modeling and analysis for optimal RCC dam design and construction

D$$ D $$‐optimal designs for multi‐response linear models with two groups

AbstractIn recent years, multi‐response linear models have gained significant popularity in various statistical applications. However, the design aspects of multi‐response linear models with group‐wise considerations have received limited attention in the literature. This paper aims to thoroughly investigate ‐optimal designs for such models. Specifically, we focus on scenarios involving two groups, where the proportions of observations for each group can be arbitrarily selected or not. Two equivalence theorems are presented to elaborate the characterization of ‐optimal designs. Additionally, we delve into the admissibility of approximate designs and establish necessary conditions for a design to be deemed admissible. Several illustrative examples are addressed to demonstrate the application of the derived theoretical results.

A medical device distribution network design strategic planning process and optimisation model

A medical device distribution network design strategic planning process and optimisation model

A Review of Data-driven Surrogate Models for Design Optimization of Electric Motors

A Review of Data-driven Surrogate Models for Design Optimization of Electric Motors

Design Optimization Model for Fixed-Sun Mirror Field Based on Monte Carlo Simulation and Particle Swarm Algorithm

Design Optimization Model for Fixed-Sun Mirror Field Based on Monte Carlo Simulation and Particle Swarm Algorithm

The Integration Mechanism of Optimization Model Design of Scholarship System and Civic and Political Education under the Strategy of Financial Aid and Parenting in Colleges and Universities

Abstract The selection of college grants is affected by many factors, but some of the influencing factors cannot be quantitatively judged at present. In order to be more fair and reasonable to the students in need of financial assistance for the review and evaluation, this paper introduces the fuzzy comprehensive evaluation method into the process to establish a fuzzy hierarchical analysis based on the college national scholarship evaluation model, the article finally through a specific example of the application of this paper based on the fuzzy comprehensive evaluation of the optimization model of the bursary system. The affiliation degree of the fuzzy comprehensive evaluation-based scholarship system constructed in this paper is (0.536,0.323,0.130,0.014), and the article concludes that Zhang’s moral education status is very good, and he is qualified to receive the scholarship.

Multidisciplinary design and optimization of intelligent Distributed Satellite Systems for EARTH observation

Recent advances in small, connected and intelligent satellite systems have created a wide range of opportunities for the adoption of intelligent Distributed Satellite Systems (iDSS) in communication, navigation and Earth Observation (EO) missions. iDSS are goal-oriented systems comprising of multiple satellites or modules that interact, communicate and/or cooperate with each other to accomplish the desired mission goals. The ability to mass-produce low-cost small satellites and contemporary developments in avionics/astrionics technology have spurred interest in iDSS, especially for Low Earth Orbit (LEO) satellite constellations and regional clusters. The SmartSat Cooperative Research Centre (CRC) and Australian space roadmap, as well as the landmark National Space Programme strategy and priorities, encompass EO. To date, insufficient progress and no conclusive outcome was made in terms of how contemporary Multidisciplinary Design Optimization (MDO) models and tools can be best tailored to the new capabilities and specificities of iDSS. The MDO of iDSS is challenging because it introduces new variables and highly non-linear interactions. In this context, we propose an MDO methodology to optimize an iDSS for persistent coverage over the entire Australian landmass. Several aspects of the iDSS are considered in this work, including the constellation model, subsystem models and the coupling interactions between different satellite subsystems and constellation design parameters. The constellation configuration, as well as the subsystems, are modelled using OpenMDAO, which is used to analyze and visualize the planned iDSS EO mission. The iDSS is then optimized using the Multidisciplinary Feasible (MDF) architecture approach and the iDSS interdependencies are numerically treated using the Nonlinear Block Gauss-Seidel (NLBGS) iterative solver. The resulting N2 diagrams are presented and the proposed solution is both spatially and temporally optimized, demonstrating that the proposed iDSS will enable near real-time persistent coverage over the entire Australian continent.

Pumpkin-based cookies formulated from optimized pumpkin flour blends: Nutritional and antidiabetic potentials

The study looked at the optimization of blends of pumpkin pulp flour, pumpkin seed, and pumpkin starch residue for the development and nutritional evaluation of cookies. 3 optimum blends, runs 12, 15, and 16 were selected out of 16 runs using Optimal Model Design of Response Surface Methodology with responses based on proximate analysis. The amino acid profile, anti-diabetic potential, physical properties, and sensory characteristics of the developed cookies were evaluated. The proximate parameters of the cookies were found to significantly (P≤ 0.05) (P ≤ 0.05) increased with the levels of pumpkin seed. The carbohydrate content of the pumpkin-based Cookies (47.20–49.12%) was significantly lower than that of the control, 100% Wheat Flour (60.29%). The ash content ranged from 6.20–8.19%, and dietary fibre, 24.39–26.9%. The amino acid profile compared well with FAO/WHO recommendations for healthy adults. The most abundant amino acids in the samples were glutamic acid, alanine, leucine, aspartate, and valine. The In-vitro Protein Digestibilities of the pumpkin-based cookies were significantly higher than that of the control sample (WFC). The pumpkin-based cookies effectively inhibited α-amylase and α-glucosidase at 59% and 69% inhibition rates respectively. The Glycemic Indices of the pumpkin-based cookies were in the range of 50–52% compared to the control (WFC) which was 61.43%, thus registering the pumpkin-based cookies as low-glycemic foods. Sensory evaluation revealed that cookies made from 60% pumpkin pulp, 24.5% pumpkin seed, and 14.4% pumpkin starch residues were generally acceptable as best among the pumpkin-based cookies.

Water Transport Modeling in a Microporous Layer for a Polymer Electrolyte Membrane Water Electrolyzer Having a Gas-Liquid Separating Interdigitated Flow Field

A novel interdigitated flow field design for polymer electrolyte membrane electrolyzers (proton exchange membrane water electrolysis cells), which has oxygen exhaust channels separated from pressurized liquid water feeding channels, has been developed for ground and space applications 1), 2). This structure separates oxygen and liquid water inside the anode of the cell. Thereby it dispenses with water circulators for bubble removal from the cell and external separators by natural or centrifugal buoyancy. We thus aim to develop a numerical model for further optimization of the cell design.Finite element modeling (COMSOL Multiphysics) of water transport is three-dimensionally conducted for the anode porous transport layer coated with a hydrophobic microporous layer (MPL) (SIGRACET 29BC, SGL Carbon Inc.) assembled with the interdigitated flow field. The MPL works to separate evolved oxygen gas exhausted in the through-plane direction and pressurized liquid water injected in the in-plane direction owing to the capillary pressure 2), 3). Prominent leakage of the liquid water to the oxygen channels has not been detected.Electrochemical kinetic parameters for the model are determined by electrochemical impedance spectra. Current-voltage measurement of the cell is also performed to validate the numerical modeling.We model the current densities and the current ratio between the reactant liquid water and water vapor at the interface between the MPL and catalyst layer (CL). The model involves fractional bubble coverage of the CL with produced oxygen gas and liquid water saturation in the MPL. The vapor evaporating from the liquid water in the MPL is assumed to be mixed with the evolved oxygen for diffusive water transport. The volumetric evaporation rate is assumed as a function of the liquid water saturation in the MPL.References1) Y. SONE, O.S. HERNANDEZ-MENDOZA, A. SHIMA, M. SATO, H. NAKAJIMA, H. MATSUMOTO, Water Electrolysis by the Direct Water Supply to the Solid Polymer Electrolyte through the Interdigitated Structure of the Electrode, Electrochemistry. 89 (2021) 138–140. https://doi.org/10.5796/electrochemistry.20-00145.2) H. NAKAJIMA, V. VEDIYAPPAN, H. MATSUMOTO, M. SATO, O.S. MENDOZA-HERNANDEZ, A. SHIMA, Y. SONE, Water Transport Analysis in a Polymer Electrolyte Electrolysis Cell Comprised of Gas/Liquid Separating Interdigitated Flow Fields, Electrochemistry. 90 (2022) 017002. https://doi.org/10.5796/electrochemistry.21-00097.3) H. Nakajima, S. Iwasaki, T. Kitahara, Pore network modeling of a microporous layer for polymer electrolyte fuel cells under wet conditions, J. Power Sources. 560 (2023) 232677. https://doi.org/10.1016/j.jpowsour.2023.232677.AcknowledgmentsThis study is based on results obtained from a project, JPNP21014, commissioned by the New Energy and Industrial Technology Development (NEDO).

Whether the off-design characteristics of equipment should be considered in integrated energy system optimization design models – A case study

The operational performance of integrated energy systems (IESs) varies with their configuration. The equipment model directly influences the capacity configuration of IESs. The conventional static model assumes that equipment efficiency is constant, ignoring its off-design characteristics. For this reason, this paper establishes a dynamic model considering the off-design characteristics of the equipment. Based on the dynamic and static models, bi-level optimization models with the minimum total cost as the optimization objective are established to optimize the configuration of IESs, and the optimization results are System 1 and System 2, respectively. Then, the operational performance of the two systems under the dynamic optimal scheduling model is compared. The results demonstrate that the capacity of the absorption chiller (ABC), combined heating and power (CHP) unit in System 1 are larger than in System 2 owing to the difference in equipment models, whereas the capacity of ground source heat pumps (GSHPs) shows the opposite trend. The larger capacity of the GSHP increases the grid power consumption of System 2 but also reduces its operating efficiency. The greater operation energy consumption and grid power consumption make the operating cost, carbon tax, and total cost of System 2 under the design condition higher than that of System 1, with an increased rate of 1.38%, 3.47%, and 1.14%, respectively. As with the design condition, the carbon tax, operating cost, and total cost of System 2 are higher than those of System 1 under both summer and winter operating conditions, particularly under summer operating conditions, where the carbon tax, operating cost, and total cost increase by 2.27%, 1.24%, and 0.88% respectively. Even if the energy price changes, the carbon tax, operating cost and total cost of System 2 in a typical year are still greater than those of System 1. Therefore, it is necessary to consider the off-design characteristics of equipment in the bi-level optimization design model.

Retracted: Improved Blockchain Technology for Performance Optimization Model Design of Sports Clubs

Retracted: Improved Blockchain Technology for Performance Optimization Model Design of Sports Clubs

An interactive tool for designing efficient toxicology experiments.

The design of dose-response experiments is an important part of toxicology research. Efficient design of these experiments requires choosing optimal doses and assigning the correct number of subjects to those doses under a given criterion. Optimal design theory provides the tools to find the most efficient experimental designs in terms of cost and statistical efficiency. However, the mathematical details can be distracting and make these designs inaccessible to many toxicologists. To facilitate use of these designs, we present an easy to use web-app for finding two types of optimal designs for models commonly used in toxicology. We include tools for checking the optimality of a given design and for assessing efficiency of any user-supplied design. Using state-of-the-art nature-inspired metaheuristic algorithms, the web-app allows the user to quickly find optimal designs for estimating model parameters or the benchmark dose.

A novel method for fast computation of the temperature rise and optimal design of GIL based on thermal network model

Accurate and fast computation of the temperature rise of gas-insulated transmission lines (GIL) is of great significance to its efficient operation and optimal design. This study proposes a novel method for efficient and accurate computation of the temperature rise and optimal design of GIL based on the thermal network method (TNM). The proposed TNM considers different heat transfer processes between the upper and lower parts of the GIL and the corresponding thermodynamic differential equations are derived. When applied to numerical simulation of GIL, the TNM can save more than three orders of magnitude in computational time compared to computational fluid dynamics (CFD) simulations, and good agreement with experimental data is also achieved. Then a fast optimal design model for GIL current-carrying structures is established based on the TNM, where it is convenient to consider factors including temperature rise and cost objectives, as well as electrical and mechanical field constraints. This optimal design approach circumvents the highly time-consuming electromagnetic-thermal-fluid coupled numerical computations. It is concluded that the proposed TNM provides an accurate way for temperature rise calculation and optimal design of GIL with really high efficiency.

Non-myopic multipoint multifidelity Bayesian framework for multidisciplinary design

The adoption of high-fidelity models in multidisciplinary design optimization (MDO) permits to enhance the identification of superior design configurations, but would prohibitively rise the demand for computational resources and time. Multifidelity Bayesian Optimization (MFBO) efficiently combines information from multiple models at different levels of fidelity to accelerate the MDO procedure. State-of-the-art MFBO methods currently meet two major limitations: (i) the sequential adaptive sampling precludes parallel computations of high-fidelity models, and (ii) the search scheme measures the utility of new design evaluations only at the immediate next iteration. This paper proposes a Non-Myopic Multipoint Multifidelity Bayesian Optimization (NM3-BO) algorithm to sensitively accelerate MDO overcoming the limitations of standard methods. NM3-BO selects a batch of promising design configurations to be evaluated in parallel, and quantifies the expected long-term improvement of these designs at future steps of the optimization. Our learning scheme leverages an original acquisition function based on the combination of a two-step lookahead policy and a local penalization strategy to measure the future utility achieved evaluating multiple design configurations simultaneously. We observe that the proposed framework permits to sensitively accelerate the MDO of a space vehicle and outperforms popular algorithms.

Comparing global sensitivity analysis methods for the joint thermal design parameters of a space manipulator based on the Sobol’ and PAWN

The Global Sensitivity Analysis method works well for screening and ranking impacting factors. It can help with thermal design optimization and thermal model calibration. This study compares the use of Sobol's variance-based method with PAWN's density-based method for 12 thermal design parameters (such as the properties of thermal control coating and the contact heat transfer coefficient between components) of a space manipulator joint thermal model. The two techniques have high consistent parameter sensitivity. The analysis's findings indicate that the junction electric box and shell's temperature variations are significantly influenced by the cooling surface's coating properties. The cooling surface's absorption rate has a bigger impact than emissivity does. Only the characteristics of the multilayer mask and the state of parcel coverage have a significant impact on the temperature of the joint shell. The outcomes offer technical backing for cooperative optimization in thermal design. The identical no-effect parameters are discovered to be recognized by Sobol' and PAWN at the same time, but they are ordered in different ways. The limitation of Sobol's technique, which uses variance as a sensitivity index, may be the cause of this outcome. Finally, the sensitivity response results are re-substituted into the finite element thermal model. The changing rule of temperature curve is used to further confirm the accuracy of the sensitivity results.

Cost Optimization and Estimation of Embodied Carbon in Reinforced Concrete Frame Structure

Reinforced concrete (RC) structures are one of the most common building systems around the world. Measures are being taken to reduce the construction industry’s contribution to the greenhouse gas emissions. The contribution of embodied energy of structures is also considered for more efficient operation of buildings. This study investigates the embodied carbon content for the different grades of concrete used for the design and an optimization approach for an economic design. Analysis and design of RC frame structures are done using STAAD-PRO software and cost optimization is carried out using Genetic Algorithm (GA) in MATLAB software. The considered design constraints are geometric, strength and reinforcement areas confirming to Indian Standard codes. The optimized result is used to model the RC structure in Revit Software to determine its embodied carbon content. Candidate structures are then assessed for embodied energy to determine individual relationships. This study shows the possibility to reduce the embodied carbon content of RC frame structure and the proposed optimum design model can be adopted to design commercial buildings as it yields reliable, economical, time-saving and practical designs whilst remaining compliant to given design codes.

Bayesian Φ q -optimal designs for multi-factor additive non linear models with heteroscedastic errors

This article considers Bayesian Φ q -optimal designs for multi-factor additive non linear models where model errors are heteroscedastic. For additive non linear models with a constant term, a sufficient condition is given in order to derive Bayesian Φ q -optimal product designs, which are achieved from univariate optimal designs with respect to every marginal model with a single factor. However, in the case of ignoring a constant term, an additional assumption of orthogonality is proposed to ensure that optimal designs can be found. Then, the corresponding optimal product designs can be built with the help of the equivalence theorem for the Bayesian Φ q -optimality criterion. Several examples are given to illustrate the effectiveness of theoretical results on optimal product designs.

Characterizing and predicting bluff-body solid fuel ramjet performances via shape design and multi-objective optimization model

In this work, we propose a rapid optimization approach to examine its application potential for the design and performance prediction and optimization of a solid fuel ramjet (SFRJ) with a bluff body. For this, the shape of the bluff body is parameterized first using the non-uniform rational B-spline method. We then develop a model for predicting SFRJ performances by incorporating both levy motion-gradient descent and support vector regression methods. It is found that a faster prediction is achievable, while the average error is maintained to be less than 5%. We then develop a multi-objective optimization model by considering the full thrust and minimum total pressure loss (TPL). The optimization model is examined using the non-dominated sorting genetic algorithm. A cost parameter is also created to facilitate the tradeoffs between the thrust and TPL in the Pareto front, when different bluff-body design configurations are considered. The present results reveal that an increase in the cost parameter will elevate the turbulence intensity within the SFRJs while drawing the incoming air closer to the fuel surface, resulting in an increase in thrust and regression rate, but the TPL will also increase. When prioritizing the TPL reduction in the design stage, the optimized solution reduces TPL by 50%. Meanwhile, the net thrust is shown to be decreased by less than 3.5%. Furthermore, flow-field investigation reveals that the improved performance of the optimized SFRJ is due to more uniform flow velocity gradients around the bluff body and a reduced rear vortex, resulting in reduced momentum loss. Our proposed optimization approach's robustness has been further confirmed with consistent performances, as the ramjet inlet speed varies over a broad range. It shows that our approach has great potential to be applied for the SFRJ performance prediction and optimization, being operated under various conditions.

Asymmetric flapping of a multi-segmented elastic structure

Motivated by the propulsion of animals using articulated bodies, this study experimentally investigates the deformation and torque generation of a multi-segmented structure undergoing flapping motion. The segmented structure consists of multiple rigid segments connected in a line through elastic sheets functioning as elastic hinges. To enhance the asymmetry in the deflection of the segmented structure between the power and recovery strokes, the elastic hinges are designed to bend only one way from their original position. To characterize the deflection profile of the segmented structure, new definitions are proposed for the effective bending stiffness of the entire structure and the dimensionless speed representing the relative magnitude of the fluid force acting on the structure to its internal bending force. These two quantities are used to determine the tip deflection adjusted by the discrete profile. Two typical deflection responses during the recovery stroke are identified, namely, an in-phase response and a delayed response. The difference in these deflection responses causes substantial changes in torque and thrust generation, particularly during the early stage of the subsequent power stroke. An evaluation of the torque and thrust generation performance, in terms of the net cyclic value and the degree of asymmetry between the two strokes, reveals the optimal model design and operation conditions of the segmented structure.

Integrated Sustainable Product Design With Warranty and End-of-Use Considerations

Abstract The concept of integrated sustainable product design has recently emerged, aiming to incorporate downstream life cycle performance into the initial product design to enhance sustainability. Various sustainable product design tools based on life cycle assessment or quality function deployment have been established while the impact of reliability on circular practices has received limited attention. Recognizing the critical role of product reliability in post-design performance, this paper develops a product design optimization model that considers the warranty performance and the effect of end-of-use options. The model takes into account the effect of uncertain operating conditions on product reliability. Two optimization goals including the minimization of expected unit life cycle cost and environmental impact are achieved by the model. To demonstrate the benefits of the integrated approach, the model is applied to an electric motor design problem. The results highlight that integrating end-of-use options in the early design phase leads to adjustments in component selection and reliability design. Moreover, the circular utilization of used products enables cost savings throughout the product’s life cycle and contributes to environmental impact reduction. Lastly, the study analyzes the effects of operating conditions, warranty policies, and take-back prices for used products on design decisions, providing valuable insights for product designers.