scholarly journals Optimal Design of Wavelength Selective Thermal Emitter for Thermophotovoltaic Applications

2017 ◽  
Vol 10 (1) ◽  
Author(s):  
Alok Ghanekar ◽  
Mingdi Sun ◽  
Zongqin Zhang ◽  
Yi Zheng
Keyword(s):  
Optimal Design ◽  
Silicon Dioxide ◽  
Radiative Properties ◽  
Optimal Designs ◽  
Emitter Temperature ◽  
One Dimensional ◽  
Radiated Energy ◽  
Dielectric Gratings ◽  
Thermal Emitter ◽  
Selective Thermal Emitter

We theoretically and numerically demonstrate optimal design of wavelength selective thermal emitter using one-dimensional (1D) and two-dimensional (2D) metal-dielectric gratings for thermophotovoltaic (TPV) applications. Proposed design consists of tungsten (W) and silicon dioxide (SiO2) gratings which can withstand high temperatures. Radiative properties of 1D grating were calculated using a numerical method, while effective medium approximation was used for 2D gratings. Optimal designs were obtained such that output power is maximum for GaSb photovoltaic (PV) cell at emitter temperature of 1500 K and radiated energy for longer wavelengths is limited to a low value. A constrained optimization was performed using genetic algorithm (GA) to arrive at optimal design.

scholarly journals Design and Numerical Evaluation of a Highly Selective CMOS-Compatible Mid-IR Thermal Emitter/Detector Structure Using Optical Tamm-States

Proceedings ◽  
2018 ◽  
Vol 2 (13) ◽  
pp. 1032 ◽  
Author(s):  
Gerald Pühringer ◽  
Bernhard Jakoby
Keyword(s):  
Thermal Emission ◽  
Low Cost ◽  
Slab Waveguide ◽  
One Dimensional ◽  
Detector Structure ◽  
Thermal Emitter ◽  
Cmos Compatible ◽  
On Chip ◽  
Vertical Cavity ◽  
Selective Thermal Emitter

In this work we propose and evaluate a concept for a selective thermal emitter suitable for monolithic on-chip integration suitable for fabrication by conventional CMOS-compatible processes. The concept is based on our recently presented work on vertical-cavity enhanced resonant thermal emission (VERTE). Here we present the application of this concept to a slab waveguide structure, instead of depositing extended dielectric layers forming a one-dimensional photonic crystal. We optimize the dimension by certain design considerations and geneticalgorithm optimization and demonstrate effective absorbing/emitting properties (depending on different slab heights) of such a low-cost structure by exciting so-called optical Tamm-states on the metal-dielectric interface.

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.

Momentum exchange impact damper design methodology for object-wall-collision problems

2017 ◽  
Vol 24 (14) ◽  
pp. 3206-3218
Author(s):  
Yohei Kushida ◽  
Hiroaki Umehara ◽  
Susumu Hara ◽  
Keisuke Yamada
Keyword(s):  
Optimal Design ◽  
Design Methodology ◽  
Design Parameters ◽  
Momentum Exchange ◽  
Impact Damper ◽  
One Dimensional ◽  
Practical Design ◽  
Wall Collision ◽  
Damper Design ◽  
And Control

Momentum exchange impact dampers (MEIDs) were proposed to control the shock responses of mechanical structures. They were applied to reduce floor shock vibrations and control lunar/planetary exploration spacecraft landings. MEIDs are required to control an object’s velocity and displacement, especially for applications involving spacecraft landing. Previous studies verified numerous MEID performances through various types of simulations and experiments. However, previous studies discussing the optimal design methodology for MEIDs are limited. This study explicitly derived the optimal design parameters of MEIDs, which control the controlled object’s displacement and velocity to zero in one-dimensional motion. In addition, the study derived sub-optimal design parameters to control the controlled object’s velocity within a reasonable approximation to derive a practical design methodology for MEIDs. The derived sub-optimal design methodology could also be applied to MEIDs in two-dimensional motion. Furthermore, simulations conducted in the study verified the performances of MEIDs with optimal/sub-optimal design parameters.

scholarly journals A Highly D‑efficient Spring Balance Weighing Design for an Even Number of Objects

2019 ◽  
Vol 5 (344) ◽  
pp. 17-27
Author(s):  
Małgorzata Graczyk ◽  
Bronisław Ceranka
Keyword(s):  
Optimal Design ◽  
Sufficient Conditions ◽  
Optimality Criteria ◽  
Point Of View ◽  
Necessary And Sufficient Conditions ◽  
Optimal Designs ◽  
Efficient Design ◽  
Spring Balance ◽  
Experimental Errors ◽  
Necessary And Sufficient

The problem of determining unknown measurements of objects in the model of spring balance weighing designs is presented. These designs are considered under the assumption that experimental errors are uncorrelated and that they have the same variances. The relations between the parameters of weighing designs are deliberated from the point of view of optimality criteria. In the paper, designs in which the product of the variances of estimators is possibly the smallest one, i.e. D‑optimal designs, are studied. A highly D‑efficient design in classes in which a D‑optimal design does not exist are determined. The necessary and sufficient conditions under which a highly efficient design exists and methods of its construction, along with relevant examples, are introduced.

Optimal Design of Plastic Structures for Fixed and Shakedown Loadings

1973 ◽  
Vol 40 (2) ◽  
pp. 595-599 ◽  
Author(s):  
M. Z. Cohn ◽  
S. R. Parimi
Keyword(s):  
Optimal Design ◽  
Loading Condition ◽  
Minimum Weight ◽  
Optimal Solution ◽  
Failure Criteria ◽  
Optimal Designs ◽  
Design Solution ◽  
Variable Loading ◽  
Framed Structures ◽  
A Value

Optimal (minimum weight) solutions for plastic framed structures under shakedown conditions are found by linear programming. Designs that are optimal for two failure criteria (collapse under fixed loads and collapse under variable repeated loads) are then investigated. It is found that these designs are governed by the ratio of the specified factors defining the two failure criteria, i.e., for shakedown, λs and for collapse under fixed loading, λ. Below a certain value (λs/λ)min the optimal solution under fixed loading is also optimal for fixed and shakedown loading. Above a value (λs/λ)max the optimal design for variable loading is also optimal under the two loading conditions. For intermediate values of λs/λ the optimal design that simultaneously satisfies the two criteria is different from the optimal designs for each independent loading condition. An example illustrates the effect of λs/λ on the nature of the design solution.

scholarly journals Testing parallelism for the four-parameter logistic model with D-optimal design

2020 ◽  
Vol 15 (3) ◽  
pp. 273-284
Author(s):  
Lin Ying ◽  
Hyun Seung Won
Keyword(s):  
Optimal Design ◽  
Logistic Model ◽  
Test Preparation ◽  
Test Sample ◽  
Optimal Designs ◽  
Model Parameters ◽  
Reference Standard ◽  
Response Curves ◽  
Classical Design ◽  
Intersection Union Test

In order to determine the potency of the test preparation relative to the standard preparation, it is often important to test parallelism between a pair of dose-response curves of reference standard and test sample. Optimal designs are known to be more powerful in testing parallelism as compared to classical designs. In this study, D-optimal design was implemented to study the parallelism and compare+ its performance with a classical design. We modified D-optimal design to test the parallelism in the four-parameter logistic (4PL) model using Intersection-Union Test (IUT). IUT method is appropriate when the null hypothesis is expressed as a union of sets, and by using this method complicated tests involving several parameters are easily constructed. Since D-optimal design minimizes the variances of model parameters, it can bring more power to the IUT test. A simulation study will be presented to compare the empirical properties of the two different designs.

Investigations on Optimal Design of a U-Tube Steam Generator

2010 ◽  
Author(s):  
Hui-min Qin ◽  
Chang-qi Yan ◽  
Meng Wang ◽  
Shi-jing He
Keyword(s):  
Optimal Design ◽  
Steam Generator ◽  
Optimization Techniques ◽  
Point Of View ◽  
Geometric Constraints ◽  
Optimal Designs ◽  
Optimal Method ◽  
Obvious Effect ◽  
Pressurized Water ◽  
Performance Point

Steam generator is one of the key equipments in the pressurized water reactor, from the performance point of view, it is necessary to apply optimization techniques to the design of the steam generator. In this work, the optimal designs of a U-tube steam generator (UTSG), taking minimization of the total volume and net weight as objective respectively, are carried out by considering thermohydraulic and geometric constraints using a complex-genetic algorithm (CGA). And the sensitivities of some parameters which influence the total volume and net weight of UTSG are also analyzed. Under the condition of constant secondary thermalhydraulic parameters of the steam generator, the optimal design indicates an obvious effect taking either the overall volume or the total weight of the steam generator as the objective. The optimization results show that the proposed optimal method is feasible and effective. And the results of optimal designs and sensitivity analysis would provide guidance in the engineering design of UTSG.

scholarly journals Optimal designs for group randomized trials and group administered treatments with outcomes at the subject and group level

2019 ◽  
Vol 29 (3) ◽  
pp. 797-810
Author(s):  
Mirjam Moerbeek
Keyword(s):  
Optimal Design ◽  
Randomized Trials ◽  
Smoking Prevention ◽  
Optimal Designs ◽  
Multiple Objective ◽  
Group Level ◽  
Group Randomized Trials ◽  
Treatment Conditions ◽  
The Subject ◽  
And Control

With group randomized trials complete groups of subject are randomized to treatment conditions. Such grouping also occurs in individually randomized trials where treatment is administered in groups. Outcomes may be measured at the level of the subject, but also at the level of the group. The optimal design determines the number of groups and the number of subjects per group in the intervention and control conditions. It is found by taking a budgetary constraint into account, where costs are associated with implementing the intervention and control, and with taking measurements on subject and groups. The optimal design is found such that the effect of treatment is estimated with highest efficiency, and the total costs do not exceed the budget that is available. The design that is optimal for the outcome at the subject level is not necessarily optimal for the outcome at the group level. Multiple-objective optimal designs consider both outcomes simultaneously. Their aim is to find a design that has high efficiencies for both outcome measures. An Internet application for finding the multiple-objective optimal design is demonstrated on the basis of an example from smoking prevention in primary education, and another example on consultation time in primary care.

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