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At least 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Derivative-free optimization methods

In many optimization problems arising from scientific, engineering and artificial intelligence applications, objective and constraint functions are available only as the output of a black-box or simulation oracle that does not provide derivative information. Such settings necessitate the use of methods for derivative-free, or zeroth-order, optimization. We provide a review and perspectives on developments in these methods, with an emphasis on highlighting recent developments and on unifying treatment of such problems in the non-linear optimization and machine learning literature. We categorize methods based on assumed properties of the black-box functions, as well as features of the methods. We first overview the primary setting of deterministic methods applied to unconstrained, non-convex optimization problems where the objective function is defined by a deterministic black-box oracle. We then discuss developments in randomized methods, methods that assume some additional structure about the objective (including convexity, separability and general non-smooth compositions), methods for problems where the output of the black-box oracle is stochastic, and methods for handling different types of constraints.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Operation and Optimization of Microwave-Heated Continuous-Flow Microfluidics

Microwave (MW) technology can be powerful for electrification and process intensification but limited fundamental understanding of scalability and design principles hinders its effective use. In this work, we build a continuous-flow microreactor inside a commercial single-mode MW applicator and the corresponding computational fluid dynamics model to simulate the temperature profile. The model is in good agreement with experiments for various microreactor dimensions and operating conditions. The model indicates that MW heating is greatly influenced by reactor geometry as well as the operating parameters. We observe a strong correlation between parameters and develop a gradient boost regression tree model to predict the outlet temperature accurately. This model is then applied to optimize the dimensions and operating conditions to maximize the outlet temperature and energy efficiency, resulting in a Pareto optimal. We demonstrate computationally and experimentally that it is possible to surpass the Pareto optimal and achieve an energy efficiency of ~90% or greater at temperatures relevant for liquid-phase chemistry via salting of the solvent. The present methodology can be applied to other complex MW reactors. Lastly, the combined numerical and experimental approach provides insights into and a framework for scale-up and optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2011

Steady-state simulation and optimization of an integrated gasification combined cycle power plant with CO2 capture

Integrated gasification combined cycle (IGCC) plants are a promising technology option for power generation with carbon dioxide (CO2) capture in view of their efficiency and environmental advantages over conventional coal utilization technologies. This paper presents a three-phase, top-down, optimization-based approach for designing an IGCC plant with precombustion CO2 capture in a process simulator environment. In the first design phase, important global design decisions are made on the basis of plant-wide optimization studies with the aim of increasing IGCC thermal efficiency and thereby making better use of coal resources and reducing CO2 emissions. For the design of an IGCC plant with 90% CO2 capture, the optimal combination of the extent of carbon monoxide (CO) conversion in the water-gas shift (WGS) reactors and the extent of CO2 capture in the SELEXOL process, using dimethylether of polyethylene glycol as the solvent, is determined in the first phase. In the second design phase, the impact of local design decisions is explored considering the optimum values of the decision variables from the first phase as additional constraints. Two decisions are made focusing on the SELEXOL and Claus unit. In the third design phase, the operating conditions are optimized considering the optimum values of the decision variables from the first and second phases as additional constraints. The operational flexibility of the plant must be taken into account before taking final design decisions. Two studies on the operational flexibility of the WGS reactors and one study focusing on the operational flexibility of the sour water stripper (SWS) are presented. At the end of the first iteration, after executing all the phases once, the net plant efficiency (HHV basis) increases to 34.1% compared to 32.5% in a previously published study (DOE/NETL-2007/1281; National Energy Technology Laboratory, 2007). The study shows that the three-phase, top-down design approach presented is very useful and effective in a process simulator environment for improving efficiency and flexibility of IGCC power plants with CO2 capture. In addition, the study identifies a number of key design variables that has strong impact on the efficiency of an IGCC plant with CO2 capture.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2011

Optimizing luminescent solar concentrator design

Luminescent Solar Concentrators (LSCs) use fluorescent materials and light guides to convert direct and diffuse sunlight into concentrated wavelength-shifted light that produces electrical power in small photovoltaic (PV) cells with the goal of significantly reducing the cost of solar energy utilization. In this paper we present an optimization analysis based on the implementation of a genetic algorithm (GA) subroutine to a numerical ray-tracing Monte Carlo model of an LSC, SIMSOLAR-P. The initial use of the GA implementation in SIMSOLAR-P is to find the optimal parameters of a hypothetical ‘‘perfect luminescent material’’ that obeys the Kennard Stepanov (K-S) thermodynamic relationship between emission and absorption. The optimization balances the efficiency losses in the wavelength shift and PV conversion with the efficiency losses due to re-scattering of light out of the collector. The theoretical limits of efficiency are provided for one, two and three layer configurations; the results show that a single layer configuration is far from optimal and adding a second layer in the LSC with wavelength shifted material in the near infrared region significantly increases the power output, while the gain in power by adding a third layer is relatively small. Here, the results of this study provide a theoretical upper limit to the performance of an LSC and give guidance for the properties required for luminescent materials, such as quantum nanocrystals, to operate efficiently in planar LSC configurations

14 SOLAR ENERGY↗
DOE OSTI2017

Development and Implementation of an Optimization Model for Hydropower and Total Dissolved Gas in the Mid-Columbia River System

Managing energy, water, and environmental priorities and constraints within a cascade hydropower system is a challenging multiobjective optimization effort that requires advanced modeling and forecasting tools. Within the mid-Columbia River system, there is currently a lack of specific solutions for predicting how coordinated operational decisions can mitigate the impacts of total dissolved gas (TDG) supersaturation while satisfying multiple additional policy and hydropower generation objectives. In this study, a reduced-order TDG uptake equation is developed that predicts tailrace TDG at seven hydropower facilities on the mid-Columbia River. The equation is incorporated into a general multiobjective river, reservoir, and hydropower optimization tool as a prioritized operating goal within a broader set of system-level objectives and constraints. A test case is presented to assess the response of TDG and hydropower generation when TDG supersaturation is optimized to remain under state water-quality standards. Satisfaction of TDG as an operating goal is highly dependent on whether constraints that limit TDG uptake are implemented at a higher priority than generation requests. According to the model, an opportunity exists to reduce TDG supersaturation and meet hydropower generation requirements by shifting spillway flows to different time periods. In conclusion, a coordinated effort between all project owners is required to implement systemwide optimized solutions that satisfy the operating policies of all stakeholders.

13 HYDRO ENERGY↗
DOE OSTI2011

Constraint Optimization Problem For The Cutting Of A Cobalt Chrome Refractory Material

This paper shows a complete approach to solve a given problem, from the experimentation to the optimization of different cutting parameters. In response to an industrial problem of slotting FSX 414, a Cobalt-based refractory material, we have implemented a design of experiment to determine the most influent parameters on the tool life, the surface roughness and the cutting forces. After theses trials, an optimization approach has been implemented to find the lowest manufacturing cost while respecting the roughness constraints and cutting force limitation constraints. The optimization approach is based on the Response Surface Method (RSM) using the Sequential Quadratic programming algorithm (SQP) for a constrained problem. To avoid a local optimum and to obtain an accurate solution at low cost, an efficient strategy, which allows improving the RSM accuracy in the vicinity of the global optimum, is presented. With these models and these trials, we could apply and compare our optimization methods in order to get the lowest cost for the best quality, i.e. a satisfying surface roughness and limited cutting forces.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Optimized boundary driven flows for dynamos in a sphere

We perform numerical optimization of the axisymmetric flows in a sphere to minimize the critical magnetic Reynolds number Rm{sub cr} required for dynamo onset. The optimization is done for the class of laminar incompressible flows of von Karman type satisfying the steady-state Navier-Stokes equation. Such flows are determined by equatorially antisymmetric profiles of driving azimuthal (toroidal) velocity specified at the spherical boundary. The model is relevant to the Madison plasma dynamo experiment, whose spherical boundary is capable of differential driving of plasma in the azimuthal direction. We show that the dynamo onset in this system depends strongly on details of the driving velocity profile and the fluid Reynolds number Re. It is found that the overall lowest Rm{sub cr} Almost-Equal-To 200 is achieved at Re Almost-Equal-To 240 for the flow, which is hydrodynamically marginally stable. We also show that the optimized flows can sustain dynamos only in the range Rm{sub cr}<Rm<Rm{sub cr2}, where Rm{sub cr2} is the second critical magnetic Reynolds number, above which the dynamo is quenched. Samples of the optimized flows and the corresponding dynamo fields are presented.

42 ENGINEERING↗
DOE OSTI2013

Extended Lagrangian Born-Oppenheimer molecular dynamics in the limit of vanishing self-consistent field optimization

We present an efficient general approach to first principles molecular dynamics simulations based on extended Lagrangian Born-Oppenheimer molecular dynamics [A. M. N. Niklasson, Phys. Rev. Lett. 100, 123004 (2008)] in the limit of vanishing self-consistent field optimization. The reduction of the optimization requirement reduces the computational cost to a minimum, but without causing any significant loss of accuracy or long-term energy drift. The optimization-free first principles molecular dynamics requires only one single diagonalization per time step, but is still able to provide trajectories at the same level of accuracy as “exact,” fully converged, Born-Oppenheimer molecular dynamics simulations. The optimization-free limit of extended Lagrangian Born-Oppenheimer molecular dynamics therefore represents an ideal starting point for robust and efficient first principles quantum mechanical molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

On the robust optimization to the uncertain vaccination strategy problem

In order to prevent an epidemic of infectious diseases, the vaccination coverage needs to be minimized and also the basic reproduction number needs to be maintained below 1. This means that as we get the vaccination coverage as minimum as possible, thus we need to prevent the epidemic to a small number of people who already get infected. In this paper, we discuss the case of vaccination strategy in term of minimizing vaccination coverage, when the basic reproduction number is assumed as an uncertain parameter that lies between 0 and 1. We refer to the linear optimization model for vaccination strategy that propose by Becker and Starrzak (see [2]). Assuming that there is parameter uncertainty involved, we can see Tanner et al (see [9]) who propose the optimal solution of the problem using stochastic programming. In this paper we discuss an alternative way of optimizing the uncertain vaccination strategy using Robust Optimization (see [3]). In this approach we assume that the parameter uncertainty lies within an ellipsoidal uncertainty set such that we can claim that the obtained result will be achieved in a polynomial time algorithm (as it is guaranteed by the RO methodology). The robust counterpart model is presented.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Design and optimization of microbolometer multilayer optical cavity

Microbolometers are the most widely used detectors in long-wave infrared uncooled thermal imagers. An optical cavity is required within a microbolometer structure to increase its optical absorption. In this work we present a detailed study on the design and optimization of a microbolometer optical cavity using Essential-Macleod package. In the simulations, the cavity is considered as thin film multi-layers that form cascaded Fabry-Perot optical cavities. In the design phase, the layers structures are selected including materials and initial thickness. The absorbing layers are chosen to be vanadium-pentoxide (V{sub 2}O{sub 5}) and titanium (Ti). In the optimization phase, the designed layer thicknesses are varied to maximize optical absorption within the absorbing layers. The simulations show that Ti layer absorption dominates over V{sub 2}O{sub 5} layer. Also, the optimization proves that the air-gap cavity thickness is not simply quarter-wavelength because of the complex cascaded Fabry-Perot structure. The optimized air-gap thickness here is ≈3.5 µm at 10.6µm wavelength.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Optimization of a Nucleic Acids united-RESidue 2-Point model (NARES-2P) with a maximum-likelihood approach

Coarse-grained models are useful tools to investigate the structural and thermodynamic properties of biomolecules. They are obtained by merging several atoms into one interaction site. Such simplified models try to capture as much as possible information of the original biomolecular system in all-atom representation but the resulting parameters of these coarse-grained force fields still need further optimization. In this paper, a force field optimization method, which is based on maximum-likelihood fitting of the simulated to the experimental conformational ensembles and least-squares fitting of the simulated to the experimental heat-capacity curves, is applied to optimize the Nucleic Acid united-RESidue 2-point (NARES-2P) model for coarse-grained simulations of nucleic acids recently developed in our laboratory. The optimized NARES-2P force field reproduces the structural and thermodynamic data of small DNA molecules much better than the original force field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Nonparametric variational optimization of reaction coordinates

State of the art realistic simulations of complex atomic processes commonly produce trajectories of large size, making the development of automated analysis tools very important. A popular approach aimed at extracting dynamical information consists of projecting these trajectories into optimally selected reaction coordinates or collective variables. For equilibrium dynamics between any two boundary states, the committor function also known as the folding probability in protein folding studies is often considered as the optimal coordinate. To determine it, one selects a functional form with many parameters and trains it on the trajectories using various criteria. A major problem with such an approach is that a poor initial choice of the functional form may lead to sub-optimal results. Here, we describe an approach which allows one to optimize the reaction coordinate without selecting its functional form and thus avoiding this source of error.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

A unified free-form representation applied to the shape optimization of the hohlraum with octahedral 6 laser entrance holes

The hohlraum is very crucial for indirect laser driven Inertial Confinement Fusion. Usually, its shape is designed as sphere, cylinder, or rugby with some kind of fixed functions, such as ellipse or parabola. Recently, a spherical hohlraum with octahedral 6 laser entrance holes (LEHs) has been presented with high flux symmetry [Lan et al., Phys. Plasmas 21, 010704 (2014); 21, 052704 (2014)]. However, there is only one shape parameter, i.e., the hohlraum to capsule radius ratio, being optimized. In this paper, we build the hohlraum with octahedral 6LEHs with a unified free-form representation, in which, by varying additional shape parameters: (1) available hohlraum shapes can be uniformly and accurately represented, (2) it can be used to understand why the spherical hohlraum has higher flux symmetry, (3) it allows us to obtain a feasible shape design field satisfying flux symmetry constraints, and (4) a synthetically optimized hohlraum can be obtained with a tradeoff of flux symmetry and other hohlraum performance. Finally, the hohlraum with octahedral 6LEHs is modeled, analyzed, and then optimized based on the unified free-form representation. The results show that a feasible shape design field with flux asymmetry no more than 1% can be obtained, and over the feasible design field, the spherical hohlraum is validated to have the highest flux symmetry, and a synthetically optimal hohlraum can be found with closing flux symmetry but larger volume between laser spots and centrally located capsule.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Field emission from optimized structure of carbon nanotube field emitter array

The authors report a detail study on the emission properties of field emitter array (FEA) of micro-circular emitters of multiwall carbon nanotubes (CNTs). The FEAs were fabricated on patterned substrates prepared with an array of circular titanium (Ti) islands on titanium nitride coated tantalum substrates. CNTs were rooted into these Ti islands to prepare an array of circular emitters. The circular emitters were prepared in different diameters and pitches in order to optimize their structure for acquiring a high emission current. The pitch was varied from 0 to 600 μm, while a diameter of circular emitters was kept constant to be 50 μm in order to optimize a pitch. For diameter optimization, a diameter was changed from 50 to 200 μm while keeping a constant edge-to-edge distance of 150 μm between the circular emitters. The FEA with a diameter of 50 μm and a pitch of 120 μm was found to be the best to achieve an emission current of 47 mA corresponding to an effective current density of 30.5 A/cm{sup 2} at 7 V/μm. The excellent emission current was attributed to good quality of CNT rooting into the substrate and optimized FEA structure, which provided a high electric field on a whole circular emitter of 50 μm and the best combination of the strong edge effect and CNT coverage. The experimental results were confirmed with computer simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

An effective model for ergonomic optimization applied to a new automotive assembly line

An efficient ergonomic optimization can lead to a significant improvement in production performance and a considerable reduction of costs. In the present paper new model for ergonomic optimization is proposed. The new approach is based on the criteria defined by National Institute of Occupational Safety and Health and, adapted to Italian legislation. The proposed model provides an ergonomic optimization, by analyzing ergonomic relations between manual work in correct conditions. The model includes a schematic and systematic analysis method of the operations, and identifies all possible ergonomic aspects to be evaluated. The proposed approach has been applied to an automotive assembly line, where the operation repeatability makes the optimization fundamental. The proposed application clearly demonstrates the effectiveness of the new approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Drive-pressure optimization in ramp-wave compression experiments through differential evolution

Ramp-wave dynamic-compression experiments are used to examine quasi-isentropic loading paths in materials. The gradual and continuous increase in pressure created by ramp waves make these types of experiments ideal for studying nonequilibrium material behavior, such as solidification kinetics. In ramp-wave compression experiments, the input drive pressure to the experimental setup may be exerted through one of a number of different mechanisms (e.g., magnetic fields, gas-gun-driven impactors, or high-energy lasers) and is generally required for simulating such experiments. Yet, regardless of the specific mechanism, this drive pressure cannot be measured directly (measurements are generally taken at a location near the back of the experimental setup through a transparent window), leading to an inverse problem where one must determine the drive pressure at the front of the experimental setup (i.e., the input) that corresponds to the particle velocity (the output) measured near the back of the experimental setup. Furthermore, we solve this inverse problem using a heuristic optimization algorithm, known as differential evolution, coupled with a multiphysics, hydrodynamics code that simulates the compression of the experimental setup. By running many rounds of forward simulations of the experimental setup, our optimization process iteratively searches for a drive pressure that is optimized to closely reproduce the experimentally measured particle velocity near the back of the experimental setup. While our optimization methodology requires a significant number of hydrodynamics simulations to be conducted, many of these can be performed in parallel, which greatly reduces the time cost of our methodology. One novel aspect of our method for determining the drive pressure is that it does not require physical modeling of the drive mechanism and can thus be broadly applied to many types of ramp-compression experiments, regardless of the drive mechanism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

A Gaussian process based surrogate approach for the optimization of cylindrical targets

Simulating direct-drive inertial confinement experiments presents significant computational challenges, both due to the complexity of the codes required for such simulations and the substantial computational expense associated with target design studies. Machine learning models, and in particular, surrogate models, offer a solution by replacing simulation results with a simplified approximation. In this study, we apply surrogate modeling and optimization techniques that are well established in the existing literature to one-dimensional simulation data of a new cylindrical target design containing deuterium–tritium fuel. These models predict yields without the need for expensive simulations. We find that Bayesian optimization with Gaussian process surrogates enhances sampling efficiency in low-dimensional design spaces but becomes less efficient as dimensionality increases. Nonetheless, optimization routines within two-dimensional and five-dimensional design spaces can identify designs that maximize yield, while also aligning with established physical intuition. Optimization routines, which ignore constraints on hydrodynamic instability growth, are shown to lead to unstable designs in 2D, resulting in yield loss. However, routines that utilize 1D simulations and impose constraints on the in-flight aspect ratio converge on novel cylindrical target designs that are stable against hydrodynamic instability growth in 2D and achieve high yield.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Technoeconomic Design Optimization for Fast Reactors. Part I: Workflow Development and Case Study for Small LFR District Energy Application

The nuclear industry is developing small reactor designs that can target a variety of deployment locations and energy products. Smaller nuclear designs have traditionally struggled to handle the steep trade-offs between size and cost that have historically incentivized large reactors. This motivates computational optimization of small reactors to minimize costs and quantify the trade-off between size and cost. In this paper, the cost/size trade-off for a small fast reactor is derived using a multi-objective genetic algorithm optimization, with steady-state, transient, and cost analysis of the fast reactor being performed. Specifically, the method is demonstrated on a small 10- to 120-MW(thermal) U-Pu-Zr–fueled lead-cooled fast reactor with a 10-year core life for district energy applications, which can have a thermal load compatible with this range. The results reinforced that fast reactor cores at the lower end of this power range suffer cost penalties due to critical mass considerations. It was found that high power density cores with strong reactivity swings and many control rods were favored over designing to minimize reactivity swing. Furthermore, this contrasts with some traditional configurations designed using engineering judgment and demonstrates that optimizers can find nontraditional but realistic solutions, along with demonstrating the value of incorporating cost functions into whole-reactor design optimization.

Fast reactor↗