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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

High-dimensional control co-design of a wave energy converter with a novel pitch resonator power takeoff system

Researchers are exploring adding wave energy converters to existing oceanographic buoys to provide a predictable source of renewable power. A ”pitch resonator” power take-off system has been developed that generates power using a geared flywheel system designed to match resonance with the pitching motion of the buoy. However, the novelty of the concept leaves researchers uncertain about various design aspects of the system. This work presents a novel design study of a pitch resonator to inform design decisions for an upcoming deployment of the system. The assessment uses control co-design via WecOptTool to optimize control trajectories for maximal electrical power production while varying five design parameters of the pitch resonator. Given the large search space of the problem, the control trajectories are optimized within a Monte Carlo analysis to identify optimal designs, followed by parameter sweeps around the optimum to identify trends between the design parameters. The gear ratio between the pitch resonator spring and flywheel are found to be the most sensitive design variables to power performance. Finally, the assessment also finds similar power generation for various sizes of resonator components, suggesting that correctly designing for optimal control trajectories at resonance is more critical to the design than component sizing.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Exact Fock-State Preparation with $n^{1/4}$ Circuit Depth

Efficient, deterministic, and high-fidelity preparation of large Fock states is essential for scaling bosonic quantum technologies and exploring quantum phenomena at large excitation energies. We introduce a deterministic one-parameter (D1p) protocol that maps Fock-state preparation in an infinite-dimensional Hilbert space onto two-dimensional amplitude amplification. Starting from a coherent state with $|α|\simeq\sqrt{n}$, the initial target-state population scales as $n^{-1/2}$, yielding an iteration count and circuit depth of $\mathcal{O}(n^{1/4})$. Phase matching guarantees unit fidelity in the ideal model; remarkably, preparing $|{10^6}\rangle$ requires only 39 iterations. The protocol uses only displacements and number-selective phase operations, requires no numerical optimization, and further extends to state transfer, general superpositions, finite-dimensional systems, and multipartite entangled states. In the large-amplitude regime, its multi-target form prepares $L$-legged cat states with an iteration count determined only by $L$; cats with up to ten legs require only two iterations, independent of the coherent-state amplitude. This framework provides a broadly applicable route to highly excited bosonic states on platforms supporting these elementary controls.

Roy, Tanay [Fermilab] (ORCID:000000019442862X)↗
DOE OSTI2025

Signal amplification in a solid-state sensor through asymmetric many-body echo

Electronic spins of nitrogen–vacancy centres in diamond constitute a promising system for micro- and nanoscale magnetic sensing, because of their operation under ambient conditions, ease of placement in close proximity to sensing targets and biological compatibility. At high densities, the electronic spins interact through dipolar coupling, which typically limits but can also potentially enhance sensing performance. Here we report the experimental demonstration of many-body signal amplification in a solid-state, room-temperature quantum sensor. Our approach uses time-reversed two-axis-twisting interactions, engineered through dynamical control of the quantization axis and Floquet engineering in a two-dimensional ensemble of nitrogen–vacancy centres. We observe that optimal amplification occurs when the backward evolution time equals twice the forward evolution time, in sharp contrast to the conventional Loschmidt echo. These observations can be understood as resulting from an underlying time-reversed mirror symmetry of the microscopic dynamics, providing key insights into signal amplification and opportunities for practical entanglement-enhanced quantum sensing.

quantum information↗
NASA NTRS1997

Chaos: Understanding and Controlling Laser Instability

In order to characterize the behavior of tunable diode lasers (TDL), the first step in the project involved the redesign of the TDL system here at the University of Tennessee Molecular Systems Laboratory (UTMSL). Having made these changes it was next necessary to optimize the new optical system. This involved the fine adjustments to the optical components, particularly in the monochromator, to minimize the aberrations of coma and astigmatism and to assure that the energy from the beam is focused properly on the detector element. The next step involved the taking of preliminary data. We were then ready for the analysis of the preliminary data. This required the development of computer programs that use mathematical techniques to look for signatures of chaos. Commercial programs were also employed. We discovered some indication of high dimensional chaos, but were hampered by the low sample rate of 200 KSPS (kilosamples/sec) and even more by our sample size of 1024 (1K) data points. These limitations were expected and we added a high speed data acquisition board. We incorporated into the system a computer with a 40 MSPS (million samples/sec) data acquisition board. This board can also capture 64K of data points so that were then able to perform the more accurate tests for chaos. The results were dramatic and compelling, we had demonstrated that the lead salt diode laser had a chaotic frequency output. Having identified the chaotic character in our TDL data, we proceeded to stage two as outlined in our original proposal. This required the use of an Occasional Proportional Feedback (OPF) controller to facilitate the control and stabilization of the TDL system output. The controller was designed and fabricated at GSFC and debugged in our laboratories. After some trial and error efforts, we achieved chaos control of the frequency emissions of the laser. The two publications appended to this introduction detail the entire project and its results.

Blass, William E.↗
NASA NTRS2012

Aeroelastic Modeling of Elastically Shaped Aircraft Concept via Wing Shaping Control for Drag Reduction

Lightweight aircraft design has received a considerable attention in recent years as a means for improving cruise efficiency. Reducing aircraft weight results in lower lift requirements which directly translate into lower drag, hence reduced engine thrust requirements during cruise. The use of lightweight materials such as advanced composite materials has been adopted by airframe manufacturers in current and future aircraft. Modern lightweight materials can provide less structural rigidity while maintaining load-carrying capacity. As structural flexibility increases, aeroelastic interactions with aerodynamic forces and moments become an increasingly important consideration in aircraft design and aerodynamic performance. Furthermore, aeroelastic interactions with flight dynamics can result in issues with vehicle stability and control. Abstract This paper describes a recent aeroelastic modeling effort for an elastically shaped aircraft concept (ESAC). The aircraft model is based on the rigid-body generic transport model (GTM) originally developed at NASA Langley Research Center. The ESAC distinguishes itself from the GTM in that it is equipped with highly flexible wing structures as a weight reduction design feature. More significantly, the wings are outfitted with a novel control effector concept called variable camber continuous trailing edge (VCCTE) flap system for active control of wing aeroelastic deflections to optimize the local angle of attack of wing sections for improved aerodynamic efficiency through cruise drag reduction and lift enhancement during take-off and landing. The VCCTE flap is a multi-functional and aerodynamically efficient device capable of achieving high lift-to-drag ratios. The flap system is comprised of three chordwise segments that form the variable camber feature of the flap and multiple spanwise segments that form a piecewise continuous trailing edge. By configuring the flap camber and trailing edge shape, drag reduction could be achieved. Moreover, some parts of the flap system can be made to have a high frequency response for roll control, gust load alleviation, and aeroservoelastic (ASE) modal suppression control. Abstract The aeroelastic model of the ESAC is based on one-dimensional structural dynamic theory that captures the aeroelastic deformation of a wing structure in a combined motion that involves flapwise bending, chordwise bending, and torsion. The model includes the effect of aircraft propulsion due to wing flexibility which causes the propulsive forces and moments to couple with the wing elastic motion. Engine mass is also accounted in the model. A fuel management model is developed to describe the wing mass change due to fuel usage in the main tank and wing tanks during cruise. Abstract The model computes both static and dynamic responses of the wing structures. The static aeroelastic deflections are used to estimate the effect of wing flexibility on induced drag and the potential drag reduction by the VCCTE flap system. A flutter analysis is conducted to estimate the flutter speed boundary. Gust load alleviation via adaptive control has been recently investigated to address flexibility of aircraft structures. A multi-objective flight control approach is presented for drag reduction control. The approach is based on an optimal control framework using a multi-objective cost function. Future studies will demonstrate the potential benefits of the approach.

Aeroelasticity↗
NASA NTRS2000

Validation of a "Kane's Dynamics" Model for the Active Rack Isolation System

Many microgravity space-science experiments require vibratory acceleration levels unachievable without active isolation. The Boeing Corporation's Active Rack Isolation System (ARIS) employs a novel combination of magnetic actuation and mechanical linkages, to address these isolation requirements on the International Space Station (ISS). ARIS provides isolation at the rack (international Standard Payload Rack, or ISPR) level. Effective model-based vibration isolation requires (1) an isolation device, (2) an adequate dynamic (i.e., mathematical) model of that isolator, and (3) a suitable, corresponding controller, ARIS provides the ISS response to the first requirement. In November 1999, the authors presented a response to the second ("A 'Kane's Dynamics' model for the Active Rack Isolation System", Hampton and Beech) intended to facilitate an optimal-controls approach to the third. This paper documents the validation of that high-fidelity dynamic model of ARIS. As before, this model contains the full actuator dynamics, however, the umbilical models are not included in this presentation. The validation of this dynamics model was achieved by utilizing two Commercial Off the Shelf (COTS) software tools: Deneb's ENVISION, and Online Dynamics' AUTOLEV. ENVISION is a robotics software package developed for the automotive industry that employs 3-dimensional (3-D) Computer Aided Design (CAD) models to facilitate both forward and inverse kinematics analyses. AUTOLEV is a DOS based interpreter that is designed in general to solve vector based mathematical problems and specifically to solve Dynamics problems using Kane's method.

Beech, Geoffrey S.↗
DOE OSTI2026

Two-Dimensional Perovskite Single-Nanowire Photodetectors

High-performance microphotodetectors require materials that combine strong light–matter interaction, fast charge transport, and ambient stability. Here, we demonstrate single-nanowire devices based on the 2D perovskite (TPA3) 2 PbBr 4 , synthesized via a controlled slow-cooling self-assembly process that yields defect-minimized, anisotropic nanowires with smooth facets. These microphotodetectors exhibit ultralow dark currents (∼10 –15 A), high responsivity (up to 156 mA W –1 ), and exceptional specific detectivity (∼10 11 Jones) under near-UV (405 nm) illumination, with rise and fall times in the millisecond regime. The superior detectivity is primarily driven by the suppression of thermal noise through the material’s ultralow dark current, while the millisecond temporal response is governed by high-intensity trap-filling dynamics. The devices maintain stable operation over 4000 s of continuous on/off cycling and show remarkable ambient stability over weeks, attributed to dense crystal packing and robust organic cation layers. Furthermore, the influence of nanowire thickness on the charge collection efficiency is systematically elucidated through optical penetration depth analysis, highlighting design principles for optimizing low-dimensional perovskite photodetectors. This study introduces single 2D perovskite nanowires as a versatile platform for miniaturized, high-performance optoelectronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Reduced-dimension Bayesian optimization for model calibration of transient vapor compression cycles

Development and calibration of first-principles dynamic models of vapor compression cycles (VCCs) is of critical importance for applications that include control design and fault detection and diagnostics. Nevertheless, the inherent complexity of models that are represented by large systems of differential–algebraic equations leads to significant challenges for model calibration processes that utilize classical gradient-based methods. Bayesian optimization (BO) is a sample-efficient and gradient-free approach using a probabilistic surrogate model and optimal search over a feasible parameter space. Despite the benefits of BO in reducing computational costs, challenges remain in dealing with a high-dimensional calibration task resulting from a large set of parameters that have significant impacts on system behavior and need to be calibrated simultaneously. This paper presents a reduced-dimension BO framework for calibrating transient VCCs models where the calibration space is projected to a low-dimensional subspace for accelerating convergence of the solution algorithm and consequently reducing the number of transient simulations. The proposed approach was demonstrated via two case studies associated with different VCC applications where 10 parameters were calibrated in each case using laboratory measurements. The reduced-dimension BO framework only required 1 / 8 th of the iterations associated with a standard BO method that deals with high-dimensional calibration parameters for converged solutions and yielded comparable accuracy. Furthermore, both calibrated models revealed significant accuracy improvements compared to uncalibrated models.

Ma, Jiacheng↗
DOE OSTI2025

Sieving Hydrogen Isotopes via Machine Learning Assisted Chemical Vapor Deposition (CVD) of High‐Quality Monolayer Hexagonal Boron Nitride (h‐BN) on Iron Foils

Atomically thin two-dimensional (2D) ceramics, such as monolayer hexagonal boron nitride (h-BN), present potential for disruptive advances in separations. However, sub-atomic scale separation of hydrogen isotopes (H + /D + ) require near pristine 2D material membranes, and scalable synthesis of such high-quality h-BN comparable to mechanically exfoliated crystals remains a significant challenge. Here, we report a scalable Fe-catalyzed chemical vapor deposition (CVD) process for bottom-up synthesis of large-area, high-quality monolayer h-BN films, overcoming key limitations of conventional ammonia-based routes. By leveraging mechanistic insights and higher CVD temperatures, we suppress multilayer formation and achieve uniform monolayer h-BN coverage on commercially available Fe foils. Machine learning enables systematic exploration of the complex, multi-dimensional CVD parameter space (growth time, temperature, precursor temperature, multilayer faction, coverage), providing data-driven approaches to visualize and identify process regimes facilitating predominantly monolayer h-BN growth with minimal secondary nuclei/ad-layers. The optimized Fe-catalyzed CVD h-BN membranes show high-quality as observed by proton/deuteron (H + /D + ) selectivity ≈8.45, approaching the highest quality benchmark of mechanically exfoliated h-BN (H + /D + selectivity ≈10) as well as significantly outperforming Cu-catalyzed CVD h-BN membranes (H + /D + selectivity ≈3.62, control selectivity ≈1.7). Our work provides a scalable cost-effective route for high-quality monolayer h-BN synthesis for sub-atomic scale separations (H + /D + ) and demonstrates the broader potential of machine learning-guided optimization of CVD for advancing synthesis of 2D materials.

36 MATERIALS SCIENCE↗
NASA NTRS1990

Application of boundary layer control to HSCT low speed configuration

The feasibility of using boundary layer control (BLC) on a high speed civil transport (HSCT) high lift configuration for low speed performance improvement is studied. The possibility of using a part of the suction system previously designed for cruise laminar flow control (LFC) for low speed BLC mode was explored. A suction scheme for BLC was devised for the HSCT high lift configuration. The extent of the suction regions and levels were determined via panel method based inviscid flow analysis coupled with three-dimensional boundary layer analyses. The compatibility of the BLC suction requirements was assessed, and the modifications necessary to operate the system in both modes of operation, were determined. An assessment of the potential aerodynamic performance improvement resulting from an implementation of the BLC concept compared to an optimized simple flap configuration without BLC was made by an Euler code analysis of the simple flap configuration.

Parikh, P. G.↗
NASA NTRS2021

Thermoelectric System Economics - The Apex: New Paradigms in Manufacturing and Interface Performance Relationships Driving System Cost Optimizations

Thermoelectric energy recovery systems require cost-optimized designs with high thermal and thermoelectric (TE) performance to surmount common commercialization barriers controlling the acceptance of thermoelectric generator (TEG) systems. Recent work has addressed this requirement with new analytic tools and paradigms that allow integrated TEG cost-performance analysis and optimization. New work herein has identified the existence of optimized TE element design (i.e., TE element length) for minimizing TEG cost and provides design guidelines associated with critical thermal and electrical contact resistance effects and TE manufacturing sensitivities. Once optimum hot-side heat flux criteria are satisfied, this work highlights the tradeoffs between interface resistance effects and manufacturing cost effects in determining optimum-cost TE element lengths, and then quantifies the increase in optimum-cost TE lengths as manufacturing costs become more sensitive to TE element lengths. Optimized TE element design criteria and key non-dimensional design parameters (i.e., [𝐶′′′LTE/𝐶′′], [TE/con], [con/(TE,aveLTE)]) driving the design are presented and explained showing the interdependencies between manufacturing cost parameters and thermal and electrical interface impacts on integrated TE cost-performance analysis and design. Comprehensive TEG system cost-performance relationships clearly demonstrate the two parameters that most greatly impact the TEG system cost are heat exchanger costs ($/(W/K)) and TE hot side heat flux. Reducing heat exhanger cost from $1/(W/K) to $0.5/(W/K) can decrease TEG system cost by $2/W to $4/W depending on TE hot side heat fluxes from 4-10 W/cm2. The impact of TE hot side heat flux on TEG system cost is larger; reducing TE system cost by factors of 2-4 as TE hot side heat flux increases from 4 W/cm2 to high levels around 18 W/cm2. The levels of thermal contact resistance and electrical contact resistance required to even approach the critical TEG system cost level of $1/W are characterized by con = 1.0 x 10-10 -m2 and r = 0.1, respectively. This not only lowers TEG costs, but it also makes the TEG system costs less sensitive to TE manufacturing dependences on TE element length. New design paradigms and relationships create holistic, integrated TE performance-cost models that enhance understanding of crucial interrelationships between component costs, TE design parameters and material properties, heat exchanger design parameters, interfacial heat flux, and now thermal and electrical interface effects in minimizing TEG system costs.

Hendricks, Terry J.↗
DOE OSTI2025

Results and lessons learned from accelerating radio frequency modeling using machine learning [slides]

The “advanced tokamak” reactor concept is a leading candidate for a steady state fusion pilot plant. An advanced tokamak (AT) sustains a majority of the required plasma current with effects resulting from maintenance of the peaked pressure at the device center. This current is augmented by auxiliary current drive sources. These auxiliary actuators may consist of neutral particle beams and/or radio frequency (RF) systems such as lower hybrid current drive (LHCD) and high harmonic fast wave (HHFW) current drive using radio and microwaves from antennas. The primary focus of this work is to develop models of RF current profile control suitable for use in integrated modeling frameworks and for real-time control in experiments. Direct physics models of RF current drive can be computationally intensive. In order to achieve predictive times appropriate for the thousands of calls needed in real-time control of experiments and for use in integrated models, we will apply modern machine learning (ML) techniques to accelerate these models and interpolate their results. To generate the fast and accurate models for use in control level algorithms and integrated modeling we need to replace present models with high dimensional interpolation of their results. We will perform additional simulations across a broader parameter range for EAST and other tokamaks in different physics regimes (Alcator C-Mod, DIII-D, WEST, CFETR, ARC, ITER) and combine them into a larger database for training and testing of the ML models. Further testing of the control level models with experimental current profile data from EAST and C-Mod tokamaks will provide additional confirmation of the control level model before integration in a tokamak control system or integrated modeling suite. ML will be used to optimize the selection of training data consisting of RF current driven at different values of density profile, temperature profile, plasma current, and wavenumber. ML will also be used to facilitate classification of current drive from these input data. The output of this effort will be a validated classifier capable of determining the current drive profiles for HHFW CD and LHCD on a mille-second timescale. This will provide a breakthrough capability enabling real-time control of RF driven current profiles in experiments including ITER ICRF and use integrated modeling frameworks requiring thousands of current profile calculations in discharge simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Reinforcement Learning Control for Enhancing Marine Hydrokinetic Turbine Energy Generation

This paper proposes a reinforcement learning-based method to maximize power generation for a direct-drive marine hydrokinetic turbine. A high levelized cost of energy (LCOE) is preventative in the widespread adoption of many marine energy conversion technologies. A straightforward way to reduce LCOE is to increase conversion efficiency and ensure maximum energy generation. The proposed method utilizes a damping control methodology, varying applied generator torque via a linear relationship between the applied damping coefficient and rotor speed. A state-action-reward-state-action (SARSA) algorithm has been used to learn the optimal control action for a given flow velocity. The proposed SARSA methodology uses Gaussian radial basis functions to create a three-dimensional surface to estimate the relationship between damping coefficient, incoming flow velocity, and coefficient of power (C p ). Here, the SARSA algorithm was compared against a baseline optimal tip speed ratio controller over a year-long flow velocity case profile while considering the effects of biofouling on the turbine system, where the proposed RL method generated 0.92% more energy than the baseline.

Damp↗
DOE OSTI2024

Focused Ion Beam Tomography of Alloy 617 Corroded in Molten Chloride Salt

Materials qualification of reactor structural materials is a critical step in rapid implementation of advanced nuclear reactor technologies, particularly to assess the corrosion performance in these designs. Accelerated qualification of reactor structural materials requires incorporating powerful computational toolsets, such as phase field modelling in the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, to predict the evolution of structural materials due to corrosion. Accordingly, computational toolsets will require experimental data generated at appropriate length scales to validate accuracy. Focused ion beam (FIB) provides a high degree of control over manipulation of materials for analytical purposes, including capturing data on the evolution in the microstructure and elemental composition of materials at the mesoscale, an appropriate length scale for phase field modelling of intergranular diffusion phenomena using the MOOSE framework. For instance, the FEI Helios G4 UX dual beam plasma FIB microscope at the Irradiated Materials Characterization Laboratory (IMCL) is capable of backscatter diffraction (EBSD) and energy-dispersive x-ray spectroscopy (EDS) documenting the evolution in the microstructure and elemental composition, respectively. The Helios can perform EDS and EBSD three-dimensionally (3D) using tomography, which is then combined using different software packages to visualize 3D volumes correlating elemental composition to microstructural data. The purpose of this investigation was to develop a streamlined characterization and data processing workflow for 3D tomography studies on the FEI Helios G4 plasma FIB. The investigation is segmented into three parts: 1) Optimizing the data collection workflow, 2) identifying appropriate data processing and visualization software (i.e. DREAM.3D, MIPAR, and VGStudioMax), and 3) establishing an infrastructure for public release. The optimization of the data collection workflow is in collaboration with members of the U220 department to setup formal training on the tomography operation of the G4, through ThermoFisher Scientific, and exploring DREAM.3D, MIPAR, and VGStudioMax data processing/visualization software packages. VGStudioMax currently demonstrates the most promise for future use. Optimization of the data collection and processing workflow is still ongoing. A collaboration with INL High Performance Computing (HPC) established an open-source license for expediting the public release of FIB tomography datasets through HPC. FIB tomography data generated by the G4 will provide comprehensive data for validating 3D phase field mesoscale modelling tools within the MOOSE framework for accelerated qualification of reactor structural materials.

Copeland-Johnson, Trishelle↗
NASA NTRS1994

Multigrid one shot methods for optimal control problems: Infinite dimensional control

The multigrid one shot method for optimal control problems, governed by elliptic systems, is introduced for the infinite dimensional control space. ln this case, the control variable is a function whose discrete representation involves_an increasing number of variables with grid refinement. The minimization algorithm uses Lagrange multipliers to calculate sensitivity gradients. A preconditioned gradient descent algorithm is accelerated by a set of coarse grids. It optimizes for different scales in the representation of the control variable on different discretization levels. An analysis which reduces the problem to the boundary is introduced. It is used to approximate the two level asymptotic convergence rate, to determine the amplitude of the minimization steps, and the choice of a high pass filter to be used when necessary. The effectiveness of the method is demonstrated on a series of test problems. The new method enables the solutions of optimal control problems at the same cost of solving the corresponding analysis problems just a few times.

Arian, Eyal↗
NASA NTRS2011

Design and Evaluation of the Terminal Area Precision Scheduling and Spacing System

This paper describes the design, development and results from a high fidelity human-in-the-loop simulation of an integrated set of trajectory-based automation tools providing precision scheduling, sequencing and controller merging and spacing functions. These integrated functions are combined into a system called the Terminal Area Precision Scheduling and Spacing (TAPSS) system. It is a strategic and tactical planning tool that provides Traffic Management Coordinators, En Route and Terminal Radar Approach Control air traffic controllers the ability to efficiently optimize the arrival capacity of a demand-impacted airport while simultaneously enabling fuel-efficient descent procedures. The TAPSS system consists of four-dimensional trajectory prediction, arrival runway balancing, aircraft separation constraint-based scheduling, traffic flow visualization and trajectory-based advisories to assist controllers in efficient metering, sequencing and spacing. The TAPSS system was evaluated and compared to today's ATC operation through extensive series of human-in-the-loop simulations for arrival flows into the Los Angeles International Airport. The test conditions included the variation of aircraft demand from a baseline of today's capacity constrained periods through 5%, 10% and 20% increases. Performance data were collected for engineering and human factor analysis and compared with similar operations both with and without the TAPSS system. The engineering data indicate operations with the TAPSS show up to a 10% increase in airport throughput during capacity constrained periods while maintaining fuel-efficient aircraft descent profiles from cruise to landing.

Swenson, Harry N.↗
DOE OSTI2025

Parallel derivative-free optimization for simulation-based design of behind-the-meter energy systems

In this work, the integrated design and dispatch of behind-the-meter or distributed resources (e.g. stationary battery storage and solar PV generation) is considered. A simulation-based framework is employed, generating high-fidelity results with closed-loop predictive control at a fine resolution, at the expense of high computational cost (several minutes to a few hours per design point). To address this challenge, parallel derivative-free design methods are considered. Four methods are compared, including state-of-the-art surrogate-based methods (Radial-Basis Functions and Gaussian processes) and sampling strategies, an evolutionary-based method, and a simple sequential grid refinement method. As a case study, two types of design problem with increasing complexity are considered, namely, the design of behind-the-meter resources (three design variables) and the inclusion of grid capacity (four design variables). The second yields a constrained design problem for which violations can only be determined after solving the computationally expensive simulation. For the three-dimensional case, all methods present a good performance, achieving a solution within 1% of the optimum after the first iteration, with the sequential grid refinement exhibiting the fastest convergence and achieving the best final objective value. This indicates that the parallel evaluation of multiple sampling points may be more important than the choice of method for small decision spaces. For the four-dimensional constrained case, the Genetic Algorithm presents the best tradeoff between performance and computational effort, while the rough objective function terrain generated by constraint violation penalties reduces the performance of surrogate-based methods. Contour plots with flat regions indicate flexibility in the optimal design and highlight the importance of characterizing the solution space.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1972

Aeroelastic optimization of a panel in high Mach number supersonic flow.

Solution for a least-weight skin thickness distribution for a panel with a flutter parameter constraint. This panel weighs less than any similar constant thickness panel, but has the same critical supersonic panel flutter parameter. The panel rests on simple supports and is of sandwich construction. The span to chord ratio is large enough that the inertial, elastic, and aerodynamic behavior is one-dimensional. The Mach number is great enough that the aerodynamic forces acting on the upper panel surface may be accurately described by quasi-steady, linearized, supersonic aerodynamic theory. The final optimum design is obtained from theoretical and numerical methods adapted from optimal control theory. The results of this investigation show that the optimal panel thickness distribution is symmetric about the panel chord midpoint. Compared to a reference panel with constant thickness, optimum panels are found to be nearly 12% lighter.

Weisshaar, T. A.↗