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Results for “Design 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.

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

Model-based Design Optimization to Achieve the Performance Goals (16.0 SEER/9.5 HSPF), Developing Heat Pump by Using Low-GWP Refrigerants and 5 mm Diameter Tubes

Usage of low-GWP refrigerants can reduce the Green House Gas (GHG) emission of HVAC systems. Our research in previous milestone report has shown that using heat exchangers with 5 mm diameter tubes instead of 9 mm diameter tubes is a promising solution to meet the performance goals of heat pump using low-GWP refrigerants. In addition, the 5mm tube heat exchangers can lead to lower system refrigerant charge and as a result, reduce environmental impact further. However, shifting to small tube diameters requires in-depth heat exchanger design optimization to adapt to the transition to low-GWP refrigerants. In the 2nd quarter of FY21, we conducted multi-objective optimizations using Particle Swarm Optimization algorithm on a residential 5-ton air source heat pump to investigate the potential system performance improvements and material savings. 4 low-GWP refrigerants, ARM20A, ARM20B, R454A and R454C are investigated in this study. The objectives of the optimization are to minimize the heat pump material cost and to maximize the system performance simultaneously. As a result, the HXs material cost is reduced by up to 77% according to the copper and aluminum material price in current market. Under heating mode operation, the smart 4-way valve guarantees that the optimal low-GWP systems maintain or outperform the heating performance of the R410A baseline system. The model-based design optimization yields 18.3-18.9 SEER and 10.6-11.9 HSPF for optimal systems using different low-GWP refrigerants. The initial performance goals (16.0 SEER/9.5 HSPF) are achieved. Furthermore, up to 50% system refrigerant charge reduction is possible in the optimized low-GWP heat pump system using ARM20B. And 91%-95% predicted life-time direct CO 2 emission reduction is achieved by using the optimal 5mm tube low-GWP heat pumps. The significant material saving, charge reduction and direct CO 2 emission reduction help in reducing the environmental impacts of heat pump systems. The optimal heat exchangers resulting from this research can fit into the original baseline indoor and outdoor fan-coil unit. This can reduce the retrofitting effort by minimizing the change in manufacturing and installation of the heat pumps and guarantee the compatibility with end-users’ house structure. Finally, the new products can be easily accepted by manufacturers and end-users.

42 ENGINEERING↗
DOE OSTI2018

Modeling and Optimal Design of Absorbent Enhanced Ammonia Synthesis

Synthetic ammonia produced from fossil fuels is essential for agriculture. However, the emissions-intensive nature of the Haber–Bosch process, as well as a depleting supply of these fossil fuels have motivated the production of ammonia using renewable sources of energy. Small-scale, distributed processes may better enable the use of renewables, but also result in a loss of economies of scale, so the high capital cost of the Haber–Bosch process may inhibit this paradigm shift. A process that operates at lower pressure and uses absorption rather than condensation to remove ammonia from unreacted nitrogen and hydrogen has been proposed as an alternative. In this work, a dynamic model of this absorbent-enhanced process is proposed and implemented in gPROMS ModelBuilder. This dynamic model is used to determine optimal designs of this process that minimize the 20-year net present cost at small scales of 100 kg/h to 10,000 kg/h when powered by wind energy. The capital cost of this process scales with a 0.77 capacity exponent, and at production scales below 6075 kg/h, it is less expensive than the conventional Haber–Bosch process.

10 SYNTHETIC FUELS↗
DOE OSTI2014

Quantum dot ternary-valued full-adder: Logic synthesis by a multiobjective design optimization based on a genetic algorithm

A methodology is proposed for designing a low-energy consuming ternary-valued full adder based on a quantum dot (QD) electrostatically coupled with a single electron transistor operating as a charge sensor. The methodology is based on design optimization: the values of the physical parameters of the system required for implementing the logic operations are optimized using a multiobjective genetic algorithm. The searching space is determined by elements of the capacitance matrix describing the electrostatic couplings in the entire device. The objective functions are defined as the maximal absolute error over actual device logic outputs relative to the ideal truth tables for the sum and the carry-out in base 3. The logic units are implemented on the same device: a single dual-gate quantum dot and a charge sensor. Their physical parameters are optimized to compute either the sum or the carry out outputs and are compatible with current experimental capabilities. The outputs are encoded in the value of the electric current passing through the charge sensor, while the logic inputs are supplied by the voltage levels on the two gate electrodes attached to the QD. The complex logic ternary operations are directly implemented on an extremely simple device, characterized by small sizes and low-energy consumption compared to devices based on switching single-electron transistors. The design methodology is general and provides a rational approach for realizing non-switching logic operations on QD devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Networked Microgrid Optimal Design and Operations Tool: Regulatory and Business Environment Study

Microgrids aim to increase the resilience of the electric supply to the loads within the microgrid through the ability to disconnect from the distribution utility in the event of a power outage and by supplying power to the microgrid loads from a combination of multiple power generation assets and storage systems. Microgrids can also improve reliability at the distribution level by reducing the load on the system under stress conditions. Networking two or more microgrids has the potential to increase reliability and resilience at a reduced cost by taking advantage of economies of scale and increasing the diversity of the generation assets and loads. This report is part of a collaborative effort among several U.S. Department of Energy national laboratories to develop a networked microgrid (NMG) Optimal Design and Operations (OD&O) tool. This tool addresses the goal defined in the Grid Modernization Multi-Year Program Plan to develop a suite of tools that addresses functional requirements for system optimal design and the operations of NMGs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

The Mechanical Design Optimization of a High Field HTS Solenoid

This paper describes the conceptual design optimization of a large aperture, high field (24 T at 4 K) solenoid for a 1.7 MJ superconducting magnetic energy storage device. The magnet is designed to be built entirely of second generation (2G) high temperature superconductor tape with excellent electrical and mechanical properties at the cryogenic temperatures. The critical parameters that govern the magnet performance are examined in detail through a multiphysics approach using ANSYS software. The analysis results formed the basis for the performance specification as well as the construction of the magnet.

Lalitha, SL↗
DOE OSTI2019

Comparing D-optimal designs with common mixture experimental designs for logistic regression

Mixture experiments are used in applications where the proportion of mixing components affects a response variable, such as in studies involving chemical formulations. In many applications, the response is dichotomous or binary (e.g., pass or fail) and a concern for researchers is how to efficiently and informatively design such experiments. A naive approach is to use design recommendations derived from linear normal-theory models with constant variance. In this research, we investigate the potential risks of such designs by comparing them to D-optimal mixture designs for binary responses and evaluating the D-efficiency of these design alternatives for several parameter subspaces. Standard designs for normal theory models generally do not work well for binary responses due to the tendency of these designs to favor boundary points. In addition, D-optimal mixture designs for binary responses tend to locate design points in the region where the magnitude of predicted response probabilities are moderate. Lastly, we recommend that researchers pay close attention to what is known about the characteristics of the underlying process models in selecting appropriate mixture designs for binary-response applications.

D-optimality↗
DOE OSTI2025

HFIR LEU High Density Silicide Dispersion Optimized Design Steady-State Heat Transfer Analyses

Steady-state heat transfer simulations of the Oak Ridge National Laboratory High Flux Isotope Reactor (HFIR) with the low-enriched uranium (LEU) high-density silicide dispersion Optimized fuel design were performed to support comprehensive performance and safety metric studies concerning this design. The LEU Optimized design operates at 95 MW to maintain HFIR’s current highly enriched uranium (HEU) core performance level at 85 MW. Full cycle Mode 1 full flow Case 1 (inlet temperature), Case 2 (flux-to-flow), and Case 3 (inlet pressure) safety limit analyses were performed to assess the margins to critical heat flux. Under the prescribed conditions, this LEU design meets the safety limit and limiting control setting requirements outlined in HFIR’s documented safety analysis; however, the safety margins are less than those for the 85 MW HEU core, and several assumptions were made where fuel fabrication and qualification data are currently lacking for the silicide fuel design. Effects of changes to pertinent fuel fabrication assumptions and uncertainty factors on thermal safety margins were also evaluated, showing that the margins are sensitive to many of these parameters. Power and pressure perturbations were also performed, indicating that significant steady-state thermal margins could be gained by increasing the coolant inlet pressure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Manufacturability-based optical design optimization for advanced Kirkpatrick–Baez X-ray focusing mirrors

The advanced Kirkpatrick–Baez (AKB) mirror setup is an effective and compelling solution to provide stable X-ray nano-focusing for synchrotron radiation or free-electron laser beamlines. We propose an AKB mirror design optimization approach to mitigate the difficulties associated with mirror fabrication by minimizing the total slope ranges of the four curved mirrors while achieving the expected focusing performance. In the optimization, we have considered geometry constraints to ensure the beam acceptance with the required clear aperture, the diffraction-limited focal size with the adequate numerical aperture, and the desired mirror gaps for adjustment and the necessary working distance for the sample stage. Additionally, practical constraints linked to mirror metrology and fabrication, such as mirror length limits and curvature uncertainty in measurement, are taken into account. Furthermore, progressive objective optimization eliminates the need for any initial guess, fully automating the AKB optimization process. This approach facilitates the development of an elegant Wolter-I or Wolter-III type AKB design solution that satisfies these multiple constraints. In cases where constraints cannot be simultaneously satisfied, the optimization results provide valuable insights into areas where trade-offs need to be considered. Simulations with ray tracing and wavefront propagation validate the optimized AKB design showing high tolerance to the beam incident angle.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Transfer learning driven design optimization for inertial confinement fusion

Transfer learning is a promising approach to create predictive models that incorporate simulation and experimental data into a common framework. In this technique, a neural network is first trained on a large database of simulations and then partially retrained on sparse sets of experimental data to adjust predictions to be more consistent with reality. Previously, this technique has been used to create predictive models of Omega [Humbird et al., IEEE Trans. Plasma Sci. 48, 61–70 (2019)] and NIF [Humbird et al., Phys. Plasmas 28, 042709 (2021); Kustowski et al., Mach. Learn. 3, 015035 (2022)] inertial confinement fusion (ICF) experiments that are more accurate than simulations alone. Here, in this work, we conduct a transfer learning driven hypothetical ICF campaign in which the goal is to maximize experimental neutron yield via Bayesian optimization. The transfer learning model achieves yields within 5% of the maximum achievable yield in a modest-sized design space in fewer than 20 experiments. Furthermore, we demonstrate that this method is more efficient at optimizing designs than traditional model calibration techniques commonly employed in ICF design. Such an approach to ICF design could enable robust optimization of experimental performance under uncertainty.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Design, optimization and critical analysis of graphene based surface plasmon resonance sensor for DNA hybridization

In this paper, the design, optimization and critical analysis of Surface Plasmon Resonance sensor is presented, which works on angular interrogation method. It comprises of five layers which are “Prism–Copper–Germanium–Graphene–Sensing medium”. The influence of the chemical potential (µ{sub c}) of graphene on the sensor performance has been studied in detail. Thickness of all the layers has been optimized. Remarkable results are achieved for the optimal thickness of copper and germanium layers as 50 nm and 6 nm respectively, while two layers of graphene having µ{sub c} of 0.5 eV are introduced to boost-up the performance. Best results in terms of detection accuracy, sensitivity and quality factor have been achieved that fulfill the necessary requirements for good sensing applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Selecting a near-optimal design for multiple criteria with improved robustness to different user priorities

In a decision-making process, relying on only one objective can often lead to oversimplified decisions that ignore important considerations. Incorporating multiple, and likely competing, objectives is critical for balancing trade-offs on different aspects of performance. When multiple objectives are considered, it is often hard to make a precise decision on how to weight the different objectives when combining their performance for ranking and selecting designs. We show that there are situations when selecting a design with near-optimality for a broad range of weight combinations of the criteria is a better test selection strategy compared with choosing a design that is strictly optimal under very restricted conditions. Here, we propose a new design selection strategy that identifies several top-ranked solutions across broad weight combinations using layered Pareto fronts and then selects the final design that offers the best robustness to different user priorities. This method involves identifying multiple leading solutions based on the primary objectives and comparing the alternatives using secondary objectives to make the final decision. We focus on the selection of screening designs because they are widely used both in industrial research, development, and operational testing. The method is illustrated with an example of selecting a single design from a catalog of designs of a fixed size. However, the method can be adapted to more general designed experiment selection problems that involve searching through a large design space.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Ocean power technology design optimization

For this study, the National Renewable Energy Laboratory and Ocean Power Technologies (OPT) conducted a collaborative code validation and design optimization study for OPT's PowerBuoy wave energy converter (WEC). NREL utilized WEC-Sim, an open-source WEC simulator, to compare four design variations of OPT's PowerBuoy. As an input to the WEC-Sim models, viscous drag coefficients for the PowerBuoy floats were first evaluated using computational fluid dynamics. The resulting WEC-Sim PowerBuoy models were then validated with experimental power output and fatigue load data provided by OPT. The validated WEC-Sim models were then used to simulate the power performance and loads for operational conditions, extreme conditions, and directional waves, for each of the four PowerBuoy design variations, assuming the wave environment of Humboldt Bay, California. And finally, ratios of power-to-weight, power-to-fatigue-load, power-to-maximum-extreme-load, power-to-water-plane-area, and power-to-wetted-surface-area were used to make a final comparison of the potential PowerBuoy WEC designs. Lastly, the design comparison methodologies developed and presented in this study are applicable to other WEC devices and may be useful as a framework for future WEC design development projects.

16 TIDAL AND WAVE POWER↗
DOE OSTI2019

Optimal design of a single-mode trench-assisted homogeneous multicore fibre with a minimum crosstalk level

We have proposed an optimal design of five different core structures (St1 – St5) for a seven-core trench-assisted multicore fibre, whose core radius and relative core/cladding refractive index difference Δ{sub 1} are optimal for single-mode propagation. The crosstalk performance and its reduction (in dB) with respect to variations in fibre design parameters, such as cladding/trench (Δ{sub 2}) depth and trench width W{sub t} are investigated. It is shown that some fibre operational parameters, like, fibre bending radius, operating wavelength and fibre length, affect the crosstalk performance. It is found that the crosstalk and its reduction amount are extremely dependent on the values of Δ{sub 1} and Δ{sub 2}. The dispersion characteristics of the cores are investigated for all the proposed core structures and the observed dispersion is found to be about – 6 ps nm{sup −1} km{sup −1} at an operating wavelength of 1550 nm. An ultralow crosstalk (less than –100 dB per 100 km) can be achieved mainly with two proposed core structures (St4 and St5) having a suitably higher values of Δ{sub 1} along with a small core radius for single-mode propagation. The multicore fibre design with many cores (up to 55) is demonstrated to ensure a high transmission capacity. (optical fibres)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Design optimization of lightweight automotive seatback through additive manufacturing compression overmolding of metal polymer composites

With the growing demand for enhanced automotive fuel efficiency and environmental sustainability, there is a need for lightweighting automotive components through innovative design and manufacturing processes. Here, this study leverages a combination of numerical iterative design optimization and hybrid additive manufacturing–compression molding (AM-CM) technique for metal polymer composites to lightweight an automotive seatback. The AM-CM process enables robust mechanical interlocking between metals and composites, boasting high stiffness and strength with low overall density. Replacing metallic components with such metal polymer composites allows for comparable mechanical performance while significantly reducing the overall weight. First, the automotive seatback design space is reduced to critical load carrying regions using topology optimization and high stress concentration areas are identified using finite element analysis. Next, a lightweight metal polymer subcomponent is designed for a high stress concentration region. The full seatback frame with spatially heterogeneous material-specific design is then iteratively optimized to enable enhanced stiffness with minimal weight. Overall, the automotive seatback frame designed with location-specific metal, polymer, and metal polymer composite materials weighs 20% less than the metal-only design while exhibiting similar stiffness.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Optimal design of 3D borehole seismic arrays for microearthquake monitoring in anisotropic media during stimulations in the EGS collab project

Multiple U.S. national laboratories, universities and industrial collaborators are conducting collaborative research under the EGS Collab project supported by the U.S. Department of Energy, to understand the fracture creation and imaging during fracturing in enhanced geothermal systems. Microearthquake hypocenter locations and focal mechanisms are used to monitor hydraulic fracturing growth and characterization at the EGS Collab experimental site at the Sanford Underground Research Facility using seismic receivers in multiple monitoring wells. In this study, we develop a methodology for optimal design a 3D borehole seismic array for cost-effective seismic monitoring in anisotropic media using not only the relationship between receiver distributions and standard deviation errors of microearthquake hypocenter locations, but also that between receiver distributions and focal-mechanism inversion errors. Our results indicate that microearthquake hypocenter locations and focal mechanisms can be reasonably well reconstructed for the EGS Collab Experiment I using six monitoring wells, including four fracture-parallel monitoring wells and two orthogonal wells. Lastly, eight seismic receivers evenly distributed in four parallel monitoring wells or twelve receivers in all six monitoring wells are required for hypocenter location, and twelve receivers evenly distributed in six wells or sixteen receivers in four wells are needed for focal-mechanism inversion.

58 GEOSCIENCES↗
DOE OSTI2022

Optimal design of multi-stage vacuum membrane distillation and integration with supercritical water desalination for improved zero liquid discharge desalination

Herein this paper proposes a novel concept for the optimal design of multi-stage vacuum membrane distillation (VMD). Generally, a multi-stage VMD is designed with an equal temperature difference between each stage. However, such a design is energy inefficient and increases VMD area. An analytical methodology for calculating the optimal stage temperature is proposed. By selecting the optimal stage temperature, the energy efficiency and required membrane area can be potentially improved by 16% and 30%, respectively. The proposed concept applies to all heat sources, including latent, sensible, and waste heat. To illustrate the method, multi-stage VMD is integrated with the waste heat from a supercritical water desalination (SCWD) system to achieve zero liquid discharge. SCWD is an energy-intensive process, requires high-quality thermal heat (>450 °C), and exhibits high waste heat rejection. The integrated VMD-SCWD approach is approximately 50% more energy-efficient and 35% more cost-efficient than the standalone SCWD system. Compared to the commercially used brine concentrator and crystallizer, the multi-stage VMD-SCWD system is more energy efficient for feed concentrations >5%. VMD-SCWD system is 30% cheaper, due to less expensive membrane distillation modules compared to a brine concentrator. The proposed design concept can replace the brine concentrator and crystallizer as an improved alternative for a zero-liquid discharge desalination system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗