Optimizing Quantum Circuit Layout Using Reinforcement Learning
Presentation slides for Summer Internships in Science and Technology (SIST) End of Term Activities 2020.
Guy, Khalil↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Integrated floating wind farm layout design and mooring system optimization to increase annual energy production
As we cluster wind turbines in wind farms to gain energy from sites with high wind speeds, wake losses occur within the wind farm. Wake loss is a term used to describe the lower energy production of a downwind turbine that is totally or partially in the wake of an upwind turbine. To decrease wake losses inside the wind farm, the wind farm’s layout is optimized. However, a variety of factors constrain the wind farm layout optimization, such as the size of the lease area relative to the number of turbines to be placed, or the shape of the lease area. Therefore, many wind farms end up with a regular grid layout, such as the Horns Rev 1 wind farm in the North Sea. The ability of a floating offshore wind turbine (FOWT) to change its position based on the wind direction and its mooring system design presents an opportunity to further decrease wake losses in floating wind farms. In this work, we integrate the design of the FOWT mooring systems with the floating wind farm layout design with the goal of increasing the farm’s annual energy production. We use the Horns Rev 1 wind farm as a case study to demonstrate our method. The results show that allowing the FOWT to relocate can decrease wake losses up to 18%. Moreover, the newly developed mooring systems are less stiff and therefore allow larger motion of the FOWT; hence, the material cost of the mooring system decreases by an estimated 17%.
17 WIND ENERGY↗
Wind farm turbine type and placement optimization
The layout of turbines in a wind farm is already a challenging nonlinear, nonconvex, nonlinearly constrained continuous global optimization problem. Here we begin to address the next generation of wind farm optimization problems by adding the complexity that there is more than one turbine type to choose from. The optimization becomes a nonlinear constrained mixed integer problem, which is a very difficult class of problems to solve. Furthermore, this document briefly summarizes the algorithm and code we have developed, the code validation steps we have performed, and the initial results for multi-turbine type and placement optimization (TTP_OPT) we have run.
17 WIND ENERGY↗
Solar Field Layout and Aimpoint Strategy Optimization
The existing methods that determine heliostat aiming strategies for concentrating solar power (CSP) central receiver plants typically use heuristics and/or are computationally expensive, and they lack flexibility for different desired flux profiles and receiver geometries. Because of the interaction between layout and aimpoint strategy, considering the former without accounting for the latter may yield solutions with superfluous heliostats that cannot be used efficiently without compromising receiver flux constraints. To that end, we develop a software decision tool that uses innovative optimization methods to both optimize aimpoint strategies and improve candidate layouts for the solar collection field of a CSP central receiver plant. A CSP plant’s effectiveness relies on the optical efficiency of the solar field, which may be limited by losses due to (i) the cosine effect, (ii) atmospheric attenuation, (iii) interference (i.e., shading and blocking) between heliostats, (iv) spillage as a result of heliostat positioning and geometry, and (iv) some heliostats’ inability to direct irradiance to the receiver without damage due to excessive thermal flux. The goal of this work is to obtain optimized aiming strategies and improved solar field layouts that reduce capital cost and increase field optical efficiency and utilization, while meeting the power requirements of a given CSP receiver design. We formulate the aimpoint optimization problem as a mixed-integer linear programming model, which we then decompose into submodels that we solve in parallel. The decomposition subdivides the solar field into sections, and aimpoint strategies for each section are obtained independently of the others. To improve existing layouts, we develop a utilization-weighted efficiency metric that we use to relocate heliostats to sections of the solar field with similar efficiency and higher utilization. Finally, to connect our software to high-fidelity flux models, we develop a Python application programming interface for SolarPILOT, a mature software package that characterizes solar field performance and generates the heliostat layouts and flux maps that serve as input to our models.
14 SOLAR ENERGY↗
Adjoint Optimization of Wind Farm Layouts for Systems Engineering Analysis
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17 WIND ENERGY↗
MDTM: Optimizing Data Transfer using Multicore-Aware I/O Scheduling [Slides]
Outline - Background & Motivation; MDTM Description & Design; Evaluation of MDTM; Conclusion.
Zhang, Liang↗
STUDY OF THE DESIGN REPRESENTATION METHODS FOR THE OPTIMIZATION OF MULTI-LAYER COMPOSITE STRUCTURES
The purpose of multi-layer composite structure optimization is to find the optimal composite layout, such that superior structure performances and lightweight can be achieved. However, the existing optimization methods have a low efficiency when applied to the multi-component, multi-layer composite structure. Such low efficiency is caused by the high dimensionality and the inherent shortcomings of the existing design representation methods. In this work, two composite layout representation methods are compared to better understand their impacts on optimization. The root cause of the low efficiency is identified, and its influences are also quantified using three metrics. Furthermore, a new Representation-Switch Optimization (RSO) strategy is proposed. This strategy improves the search efficiency by switching the design representation methods during the optimization process. Three benchmark studies, two mathematical examples and one real engineering example, are conducted to demonstrate the impact of design representation methods on the optimization results, as well as the effectiveness of the proposed optimization strategy.
Xu, Hongyi↗
Sensitivity of Wind Farm Output to Wind Conditions, Land Configuration, and Installed Capacity, Under Different Wake Models; Article No. 061403
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24 POWER TRANSMISSION AND DISTRIBUTION↗
Systematic Layout Planning of a Radiology Reporting Area to Optimize Radiologists’ Performance
Optimizing radiologists’ performance is a major priority for managers of health services/systems, since the radiologists’ reporting activity imposes a severe constraint on radiology productivity. Despite that, methods to optimize radiologists’ reporting workplace layout are scarce in the literature. This study was performed in the Radiology Division (RD) of an 850-bed University-based general hospital. The analysis of the reporting workplace layout was carried out using the systematic layout planning (SLP) method, in association with cluster analysis as a complementary tool in early stages of SLP. Radiologists, architects, and hospital managers were the stakeholders consulted for the completion of different stages of the layout planning process. A step-by-step description of the proposed methodology to plan an RD reporting layout is presented. Clusters of radiologists were defined using types of exams reported and their frequency of occurrence as clustering variables. Sectors with high degree of interaction were placed in proximity in the new RD layout, with separation of noisy and quiet areas. Four reporting cells were positioned in the quiet area, grouping radiologists by subspecialty, as follows: cluster 1-abdomen; cluster 2-musculoskeletal; cluster 3-neurological, vascular and head & neck; cluster 4-thoracic and cardiac. The creation of reporting cells has the potential to limit unplanned interruptions and enhance the exchange of knowledge and information within cells, joining radiologists with the same expertise. That should lead to improvements in productivity, allowing managers to more easily monitor radiologists’ performance.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
The theoretical ultimate magnetoelectric coefficients of magnetoelectric composites by optimization design
This paper investigates what is the largest magnetoelectric (ME) coefficient of ME composites, and how to realize it. From the standpoint of energy conservation, a theoretical analysis is carried out on an imaginary lever structure consisting of a magnetostrictive phase, a piezoelectric phase, and a rigid lever. This structure is a generalization of various composite layouts for optimization on ME effect. The predicted theoretical ultimate ME coefficient plays a similar role as the efficiency of ideal heat engine in thermodynamics, and is used to evaluate the existing typical ME layouts, such as the parallel sandwiched layout and the serial layout. These two typical layouts exhibit ME coefficient much lower than the theoretical largest values, because in the general analysis the stress amplification ratio and the volume ratio can be optimized independently and freely, but in typical layouts they are dependent or fixed. To overcome this shortcoming and achieve the theoretical largest ME coefficient, a new design is presented. In addition, it is found that the most commonly used electric field ME coefficient can be designed to be infinitely large. We doubt the validity of this coefficient as a reasonable ME effect index and consider three more ME coefficients, namely the electric charge ME coefficient, the voltage ME coefficient, and the static electric energy ME coefficient. We note that the theoretical ultimate value of the static electric energy ME coefficient is finite and might be a more proper measure of ME effect.
36 MATERIALS SCIENCE↗
Examining the Impact of Data Layout on Tape on Data Recall Performance for ATLAS
Increases in data volumes are forcing high-energy and nuclear physics experiments to store more frequently accessed data on tape. Extracting the maximum performance from tape drives is critical to make this viable from a data availability and system cost standpoint. The nature of data ingest and retrieval in an experimental physics environment make achieving high access performance difficult given the inherent limitations of magnetic tape. Tailoring the layout of data on tape is one key to improving read performance. This paper highlights the work in progress to characterize ATLAS data ingested in the tape system, understand how data layout, i.e. file co-location on tape and file distribution over tapes, affect read performance and how optimal data layout might be achieved in a production environment.
99 GENERAL AND MISCELLANEOUS↗
Incorporating Wind Turbine Choice in High-Resolution Geospatial Supply Curve and Capacity Expansion Models
To achieve national decarbonization goals, U.S. annual deployment of wind energy will need to increase by at least fivefold compared to the recent past. Modeling and analysis frameworks can help inform where and how wind energy deployment might occur and thereby help enable the achievement of decarbonization goals. However, most prior wind energy modeling and analysis studies rely on generalized representations of wind energy technologies. Since wind energy technology advancements are expected to increase the competitiveness of wind energy, it is important to incorporate more detailed representations of turbine technology into wind energy modeling. Here we present a new method that incorporates wind turbine choice into the technology representation of land-based wind energy in long-term planning models. Our method integrates three previously published modeling and analysis capabilities: 1) bottom-up cost modeling to estimate future technology costs, 2) geospatial modeling to represent siting decisions, and 3) power sector modeling to evaluate potential deployment. We refer to this approach as a "customized turbine choice" methodology because it creates a composite turbine scenario by choosing from multiple wind turbine technologies—using site-specific optimized turbine layout and selecting the least-cost technology at each location. We demonstrate the capabilities of this new modeling pipeline by examining how the selection of four different wind turbine configurations might evolve from 2021 through 2040. Our results show that using our customized turbine choice methodology could lead to higher estimates for wind future deployment, which indicates that more simplified modeling might underestimate the role that wind energy could play in meeting decarbonization goals. Future research is needed to further explore the implications of turbine choice and to better inform technology researchers, original equipment manufacturers, and other wind industry stakeholders about the market potential of different wind turbine technologies.
17 WIND ENERGY↗
Progress on Optimizing Wind Farms and Rotor Designs Using Adjoints
Modern wind plants are increasingly tasked with multiple performance objectives. In addition to designing plants that maximize power output and minimize the levelized cost of energy (LCOE), the design and operation of wind plants is increasingly influenced by challenges regarding grid integration of variable generation renewables. This places a growing emphasis on making wind plants more controllable and predictable. WindSE is a Reynolds-averaged Navier-Stokes (RANS) model designed around analytical gradient and adjoint methods, with the ability to capture terrain-induced effects, as shown in Figure 1. The recent addition of an unsteady solver with an actuator line method (ALM) and ongoing work to enable massively parallel optimizations gives it a unique niche to explore coupled plant-level controls and design problems. This code is an open source python package built on the FEniCS framework that utilizes fast, parallel PETSc solvers to model fluid flow throughout wind-farm scale domains. Two recent studies performed using WindSE demonstrate the capability to optimize under a wide variety of flow conditions and objective functions. In the first, we present an optimization focused on modifying the layout of a wind farm with a fixed number of turbines for maximum total power output [1]. This study highlights the ability to quickly perform simulations using the steady Navier-Stokes solver combined with rotors represented as actuator disks while also stressing the importance of capturing terrain-induced effects. Gradient-based optimization using the RANS equations is viable due to the inclusion of efficiently computed adjoint derivatives. We interpret the physical results of the optimal layout and also discuss the computational cost of scaling to larger problems. In the second study, we present the capabilities of the unsteady Navier-Stokes solver, where rotor-blade profiles represented by actuator lines are optimized to enhance wake steering effects and overall power production [2]. We quantify the wind plant performance gains obtained from this type of simultaneous control co-design optimization as compared to optimizing the blade design and yaw independently. Figure 2 shows the differences between a baseline two-turbine system and an optimized system where we fine-tune the blade chord profile. Results and challenges from each study are quickly summarized and used to motivate the current development efforts within WindSE. Current and future work is focused on enabling higher-resolution studies with more degrees of freedom through parallelization of both the simulation and optimization algorithms. We present benchmarking results to show that WindSE performs well in both weak- and strong-scaling tests and further demonstrate that the optimizer obtains the same convergence rates in both shared- and distributed-memory environments. Using larger wind farms, we can study deep-array effects within an optimization context, allowing the use of objective functions that have been previously unstudied. As an example, we present ongoing work on a blockage metric which characterizes the loss of available kinetic energy due to wake effects from multiple upstream turbines.
adjoint optimization↗
SolarPILOT: A power tower solar field layout and characterization tool
This paper develops and demonstrates a new SolarPower tower Integrated Layout and Optimization Tool (SolarPILOT). The tool uses the analytical flux image Hermite series approximation originally implemented in the DELSOL3 software developed by Sandia National Laboratory in the early 1980s. By applying the analytical model to individual heliostat images rather than large groups or zones of heliostats, SolarPILOT can characterize a wide variety of heliostat field layouts. The individual heliostat modeling approach increases computational expense in comparison with DELSOL3, so SolarPILOT implements a number of improvements to the analytical approximation method to improve model accuracy and computational efficiency. This paper discusses several of these methods, including dynamic heliostat grouping to reduce the expense of intercept factor evaluation, approximation of annual productivity with a subset of time steps throughout the year, polygon clipping to accurately calculate inter-heliostat shadowing and blocking, receiver and tower geometry optimization, and a trigonometric image transformation technique that ensures model accuracy for small heliostats. SolarPILOT also integrates a Monte-Carlo ray tracing engine (SolTrace), providing improved receiver optical modeling capability, a user-friendly front end for geometry definition, and side-by-side validation of the analytical algorithms.
14 SOLAR ENERGY↗
A general-purpose method for Pareto optimal placement of flow rate and concentration sensors in networked systems – With application to wastewater treatment plants
The advent of affordable computing, low-cost sensor hardware, and high-speed and reliable communications have spurred installation of ubiquitous sensors in complex engineered systems. However, ensuring reliable data quality remains a challenge. Exploitation of redundancy among sensor signals can help improving the precision of measured variables, detecting the presence of gross errors, and identifying faulty sensors. The cost of sensor ownership, maintenance efforts in particular, can still be cost-prohibitive however. Maximizing the ability to assess and control data quality while minimizing the cost of ownership thus requires a careful sensor placement. To solve this challenge, in this work we develop a generally applicable method to solve the multi-objective sensor placement problem in systems governed by linear and bilinear balance equations. Importantly, the method computes all Pareto-optimal sensor layouts with conventional computational resources and requires no information about the expected sensor quality.
42 ENGINEERING↗
Ultra-thick three-dimensional interpenetrating graphene electrode architectures for high volumetric density energy storage
For electrochemical energy storage, increasing the electrode thickness is an effective approach to achieving higher energy density from a given material. However, this often compromises ion transport, leading to diminished performance. Here, in this study, we present a novel platform for fabricating complex 3D interpenetrating electrode structures via photo-polymerization 3D printing, integrated with computational structural optimization for energy storage. The platform employs an acrylate resin system infused with graphene oxide (GO), enabling high-fidelity printing of optimized porous structures and facilitating efficient electron and ion transport in ultra-thick electrodes. The optimized 3D layouts substantially enhance energy and power densities compared to conventional configurations, ensuring superior material utilization and minimal ohmic losses. Supercapacitors fabricated using this approach achieved an exceptional energy density of 4.7 Wh L−1 at a power density of 1689.0 W L−1, surpassing traditional designs. This work underscores the transformative role of structural optimization in advancing electrochemical performance and establishes a versatile pathway for developing next-generation energy storage systems with exceptional efficiency and functionality.
Wang, Zhen [University of California, Berkeley, CA↗
A multi-objective optimization model for cropland design considering profit, biodiversity, and ecosystem services
More sustainable agricultural methods are needed to alleviate the decreases in biodiversity and ecosystem services that have occurred because of industrial agriculture. One such method is the inclusion of alternative crops into croplands that can support biodiversity, reduce erosion and chemical runoff, and sequester carbon in the soil. However, the question of where such crops should be planted to balance competing economic and environmental objectives remains open. To this end, we develop a mixed-integer quadratically constrained program to optimize the layout of a cropland considering economic, biodiversity, greenhouse gas emissions, and water quality objectives. We include spatially varying fertilization as a decision variable in addition to crop establishment location. We further include the effect of core area and edges between different crops on biodiversity. To demonstrate the applicability of the model, we apply it to an example field, showing how the optimal cropland design changes as a decision-maker prioritizes different objectives and as edges have different impacts on biodiversity.
54 ENVIRONMENTAL SCIENCES↗
HOPP - Hybrid Optimization and Performance Platform
The Hybrid Optimization and Performance Platform, HOPP, is a wind + solar + battery + X design software for optimizing co-located, utility-scale hybrid plants down to the component level for different markets and technoeconomic objectives. Key technology and financial inputs to the HOPP model that inform the objective to be optimized are presented. The layout and performance integration is combined with optimal dispatch and full financial modeling within an optimization framework. With an example scenario, optimal sizing and layout results are shown in a sensitivity analysis of prices for two hybrid configurations.
batteries↗