Search NASA⌕ Search

SEARCH · Search NASA

Results for “layout optimization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The curled wake model: a three-dimensional and extremely fast steady-state wake solver for wind plant flows

Abstract. Wind turbine wake models typically require approximations, such as wake superposition and deflection models, to accurately describe wake physics. However, capturing the phenomena of interest, such as the curled wake and interaction of multiple wakes, in wind power plant flows comes with an increased computational cost. To address this, we propose a new hybrid method that uses analytical solutions with an approximate form of the Reynolds-averaged Navier–Stokes equations to solve the time-averaged flow over a wind plant. We compare results from the solver to supervisory control and data acquisition data from the Lillgrund wind plant obtaining wake model predictions which are generally within 1 standard deviation of the mean power data. We perform simulations of flow over the Columbia River Gorge to demonstrate the capabilities of the model in complex terrain. We also apply the solver to a case with wake steering, which agreed well with large-eddy simulations. This new solver reduces the time – and therefore the related cost – it takes to simulate a steady-state wind plant flow (on the order of seconds using one core). Because the model is computationally efficient, it can also be used for different applications including wake steering for wind power plants and layout optimization.

17 WIND ENERGY↗
NASA NTRS2006

The Effectiveness of TAG or Guard-Gates in SET Suppression Using Delay and Dual-Rail Configurations at 0.35 microns

Design options for decreasing the susceptibility of integrated circuits to Single Event Upset (SEU) fall into two categories: (1) increasing the critical charge to cause an upset at a particular node, and (2) employing redundancy to mask or correct errors. With decreasing device sizes on an Integrated Circuit (IC), the amount of charge required to represent a logic state has steadily reduced. Critical charge methods such as increasing drive strength or increasing the time required to change state as in capacitive or resistive hardening or delay based approaches extract a steadily increasing penalty as a percentage of device resources and performance. Dual redundancy is commonly assumed only to provide error detection with Triple Modular Redundancy (TMR) required for correction, but less well known methods employ dual redundancy to achieve full error correction by voting two inputs with a prior state to resolve ambiguity. This requires special circuits such as the Whitaker latch [1], or the guard-gate [2] which some of us have called a Transition AND Gate (TAG) [3]. A 2-input guard gate is shown in Figure 1. It is similar to a Muller Completion Element [4] and relies on capacitance at node "out" to retain the prior state when inputs disagree, while eliminating any output buffer which would be susceptible to radiation strikes. This paper experimentally compares delay based and dual rail flip-flop designs wherein both types of circuits employ guard-gates to optimize layout and performance, and draws conclusions about design criteria and suitability of each option. In both cases a design goal is protection against Single Event Transients (SET) in combinational logic as well as SEU in the storage elements. For the delay based design, it is also a goal to allow asynchronous clear or preset inputs on the storage elements, which are often not available in radiation tolerant designs.

Shuler, Robert L.↗
NASA NTRS2017

Ultra-Wideband Array in PCB for Millimeter-Wave 5G and ISM

Next generation 5G mobile architectures will take advantage of the millimeter-wave spectrum to deliver unprecedented bandwidth. Concurrently, there is a need to consolidate numerous disparate allocations into a single, multi-functional array. Existing arrays are either narrow-band, prohibitively expensive or cannot be scaled to these frequencies. In this paper, we present the first ultra-wideband millimeter-wave array to operate across the six 5G and ISM bands spanning 24-71 GHz. Critically, the array is realized using low-cost PCB. The design concept and optimized layout are presented, and fabrication and measurement considerations are discussed.

Ultra-Wideband Array↗
NASA NTRS2017

24-71 GHz PCB Array for 5G ISM

Millimeter-wave 5G mobile architectures need to consolidate disparate frequency bands into a single, multifunctional array. Existing arrays are either narrow-band, prohibitively expensive or cannot be scaled to these frequencies. In this paper, we present the first ultra-wideband millimeter wave array to operate across six 5G and ISM bands spanning 24-71 GHz. Importantly, the array is realized using low-cost PCB. The paper presents the design and optimized layout, and discusses fabrication and measurements.

5G and ISM↗
DOE OSTI2015

NREL Software Models Performance of Wind Plants (Fact Sheet)

This NREL Highlight is being developed for the 2015 February Alliance S&T Meeting, and describes NREL's Simulator for Offshore Wind Farm Applications (SOWFA) software in collaboration with Norway-based Statoil, to optimize layouts and controls of wind plants arrays.

17 WIND ENERGY↗
DOE OSTI2023

Scaling Wind Power Innovation Assessment for Rapid Energy Transition with Artificial Intelligence

Planning for energy system decarbonization requires new insights into the potential of renewable technologies, deployed at unprecedented scale, to meet urgent sustainability goals. However, limited scalability of current wind energy research tools restricts characterization of innovation impacts to isolated reference sites, challenging investment and decision making under rapid growth. We demonstrate the transformative potential of artificial intelligence (AI) to inform future technology advancement and energy systems design by leveraging a state-of-the-art surrogate model to conduct a series of fleet-wide wind plant layout optimizations for greater than 6,800 projected U.S. onshore buildout locations. We show how innovative wake steering technology can address an array of barriers to large-scale deployment and integration of wind power. Specifically, wake steering reduces required plant area by an average of 18% and could preserve upwards of 13,000 km2 for future greenfield deployment, potentially easing siting challenges associated with wind energy infrastructure. Further, by enabling reduced turbine spacing and increased energy production, flexible operations of wake steering improve levelized cost of energy, particularly for large plants and in land-constrained settings. Finally, optimizations that consider dynamic energy prices can deliver increased power production and revenue capture during high-value (often low-wind) periods, further bolstering plant economics. Our computationally efficient approach offers a pathway to accelerate nationwide geographic evaluation of innovative technologies.

graph neural networks↗
DOE OSTI2021

Objective and algorithm considerations when optimizing the number and placement of turbines in a wind power plant

Abstract. Optimizing turbine layout is a challenging problem that has been extensively researched in the literature. However, optimizing the number of turbines within a given boundary has not been studied as extensively and is a difficult problem because it introduces discrete design variables and a discontinuous design space. An essential step in performing wind power plant layout optimization is to define the objective function, or value, that is used to express what is valuable to a wind power plant developer, such as annual energy production, cost of energy, or profit. In this paper, we demonstrate the importance of selecting the appropriate objective function when optimizing a wind power plant in a land-constrained site. We optimized several different wind power plants with different wind resources and boundary sizes. Results show that the optimal number of turbines varies drastically depending on the objective function. For a simple, one-dimensional, land-based scenario, we found that a wind power plant optimized for minimal cost of energy produced just 72 % of the profit compared to the wind power plant optimized for maximum profit, which corresponded to a loss of about USD 2 million each year. This paper also compares the performance of several different optimization algorithms, including a novel repeated-sweep algorithm that we developed. We found that the performance of each algorithm depended on the number of design variables in the problem as well as the objective function.

17 WIND ENERGY↗
DOE OSTI2024

On optimizing the sensor spacing for pressure measurements on wind turbine airfoils

This research article presents a robust approach to optimizing the layout of pressure sensors around an airfoil. A genetic algorithm and a sequential quadratic programming algorithm are employed to derive a sensor layout best suited to represent the expected pressure distribution and, thus, the lift force. The fact that both optimization routines converge to almost identical sensor layouts suggests that an optimum exists and is reached. By comparing against a cosine-spaced sensor layout, it is demonstrated that the underlying pressure distribution can be captured more accurately with the presented layout optimization approach. Conversely, a 39 %–55 % reduction in the number of sensors compared to cosine spacing is achievable without loss in lift prediction accuracy. Given these benefits, an optimized sensor layout improves the data quality, reduces unnecessary equipment and saves cost in experimental setups. While the optimization routine is demonstrated based on the generic example of the IEA 15 MW reference wind turbine, it is suitable for a wide range of applications requiring pressure measurements around airfoils.

17 WIND ENERGY↗
DOE OSTI2024

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↗
DOE OSTI2016

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↗
NASA NTRS2020

Optimal Aircraft Control Surface Layouts for Maneuver and Gust Load Alleviation

The goal of this work is to conduct aeroservoelastic optimization of a high aspect ratio transport wingbox with distributed control surfaces along the trailing edge. The control surfaces are utilized for both quasi-steady maneuver load alleviation (MLA) and unsteady gust load alleviation (GLA). The optimizer dictates the sizing details of the wingbox, the steady and unsteady control surface rotations, and also the control surface layout. Layout design variables specifically dictate which control surfaces to retain, and which to remove. The objective function is to minimize the sum of the actuator weight and the structural weight, with several imposed constraints related to structural failure and actuator saturation. The optimizer’s preferences with regards to control surface layout for MLA are in strong contrast to GLA-driven designs. The GLA-driven design space also suffers from local minima not evident in the MLA space.

Stanford, Bret K.↗
DOE OSTI2021

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↗
DOE OSTI2017

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↗
DOE OSTI2018

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↗