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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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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Designing Optimal Perovskite Structure for High Ionic Conduction

Solid-oxide fuel/electrolyzer cells are limited by a dearth of electrolyte materials with low ohmic loss and an incomplete understanding of the structure-property relationships that would enable the rational design of better materials. In this work, using epitaxial thin-film growth, synchrotron radiation, impedance spectroscopy, and density-functional theory, the impact of structural parameters (i.e., unit-cell volume and octahedral rotations) on ionic conductivity is delineated in La 0.9 Sr 0.1 Ga 0.95 Mg 0.05 O 3-σ . As compared to the zero-strain state, compressive strain reduces the unit-cell volume while maintaining large octahedral rotations, resulting in a strong reduction of ionic conductivity, while tensile strain increases the unit-cell volume while quenching octahedral rotations, resulting in a negligible effect on the ionic conductivity. Calculations reveal that larger unit-cell volumes and octahedral rotations decrease migration barriers and create low-energy migration pathways, respectively. The desired combination of large unit-cell volume and octahedral rotations is normally contraindicated, but through the creation of superlattice structures both expanded unit-cell volume and large octahedral rotations are experimentally realized, which result in an enhancement of the ionic conductivity. All told, the potential to tune ionic conductivity with structure alone by a factor of ≈ 2.5 at around 600 degrees C is observed, which sheds new light on the rational design of ion-conducting perovskite electrolytes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units

Atomic structure prediction and associated property calculations are the bedrock of chemical physics. Since high-fidelity ab initio modeling techniques for computing the structure and properties can be prohibitively expensive, this motivates the development of machine-learning (ML) models that make these predictions more efficiently. Training graph neural networks over large atomistic databases introduces unique computational challenges such as the need to process millions of small graphs with variable size and support communication patterns that are distinct from learning over large graphs such as social networks. We demonstrate a novel hardware-software co-design approach to scale up the training of atomistic graph neural networks (GNN) for structure and property prediction. First, to eliminate redundant computation and memory associated with alternative padding techniques and to improve throughput via minimizing communication, we formulate the effective coalescing of the batches of variable-size atomistic graphs as the bin packing problem and introduce a hardware-agnostic algorithm to pack these batches. In addition, we propose hardware-specific optimizations including a planner and vectorization for the gather-scatter operations targeted for Graphcore’s Intelligence Processing Unit (IPU), as well as model-specific optimizations such as merged communication collectives and optimized softplus. Putting these all together, we demonstrate the effectiveness of the proposed co-design approach by providing an implementation of a well-established atomistic GNN on the Graphcore IPUs. We evaluate the training performance on multiple atomistic graph databases with varying degrees of graph counts, sizes and sparsity. Here, we demonstrate that such a co-design approach can reduce the training time of atomistic GNNs and can improve the performance by up to 1.5× compared to the baseline implementation of the model on the IPUs. Additionally, we compare our IPU implementation with a Nvidia GPU-based implementation and show that our atomistic GNN implementation on the IPUs can run 1.8× faster on average compared to the execution time on the GPUs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

AI-Based Optimal Design and Controls Can Greatly Reduce Carbon Emissions and Enhance Resilience in Residential Communities in Cold Climates

Net-zero energy residential communities are crucial for achieving decarbonization goals, but the high-penetration photovoltaic (PV) in those communities is posing challenges to the distribution grid. Traditional design and operation of net-zero communities rely on rule-of-thumb methods and may not work in complex scenarios. Artificial intelligence and machine learning methods can optimally size PV for net-zero energy, identify user preferences and usage patterns, and fully unlock the potential of distributed energy resources to address distribution grid issues.

artificial intelligence↗
DOE OSTI2014

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↗
DOE OSTI2026

Design optimization of MAPS-based detectors using a data-driven fast simulation approach

A parametric simulation tool for pixel sensors is presented. A realistic pixel response is simulated purely based on measurement input, without requiring detailed knowledge of the underlying manufacturing process. As such, it provides an efficient alternative to the use of Technology Computer-Aided Design simulations, which typically depend on proprietary process information. Due to its parametric approach, the package is fast and thus particularly useful for larger detector systems and high hit rate environments. This work presents measurements, simulation and its validation for the MALTA2 sensor. It is a small collection electrode monolithic active pixel sensor produced in the Tower 180 nm complementary metal-oxide-semiconductor imaging process. Modifications to the sensor’s periphery, mainly in the hit merger, are studied in order to optimize the performance for tracking and calorimetry. This optimization is of special interest as part of the MALTA3 sensor redesign in the 65 nm Tower Partners Semiconductor Co. process.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Magnet Design Optimization for Future Hadron Colliders

Fermilab in collaboration with other members of the US Magnet Development Program (MDP) is working on the development of accelerator magnets for future hadron colliders. A 4-layer, 15-T dipole with 60 mm aperture based on Nb3Sn Low Temperature Superconductor (LTS) has been fabricated and tested. It is an important milestone of demonstrating readiness of the LTS magnet technology for the next generation of hadron colliders. At the same time, design studies aimed at boosting the magnet performance even further with the help of High Temperature Superconductors (HTS) are under way. This paper introduces a novel magnet technology - Conductor On Molded Barrel (COMB) optimized for the HTS materials and discusses possible steps towards its demonstration.

43 PARTICLE ACCELERATORS↗
DOE OSTI2011

Theory for optimal design of waveguiding light concentrators in photovoltaic microcell arrays

Efficiency of ultrathin flexible solar photovoltaic silicon microcell arrays can be significantly improved using nonimaging solar concentrators. A fluorophore is introduced to match the solar spectrum and the low-reflectivity wavelength range of Si, reduce the escape losses, and allow the nontracking operation. In this paper we optimize our solar concentrators using a luminescent/nonluminescent photon transport model. Key modeling results are compared quantitatively to experiments and are in good agreement with the latter. Here, our solar concentrator performance is not limited by the dye self-absorption. Bending deformations of the flexible solar collectors do not result in their indirect gain degradation compared to flat solar concentrators with the same projected area.

14 SOLAR ENERGY↗
DOE OSTI2017

Hydrodynamic Design Optimization and Wave Tank Testing of a Self-Reacting Two-Body Wave Energy Converter

As worldwide energy consumption continues to increase, so does the demand for renewable energy sources. The total available wave energy resource for the United States alone is 2,640 TWh/yr; nearly two thirds of the 4,000 TWh of electricity used in the United States each year. It is estimated that nearly half of that available energy is recoverable through wave energy conversion techniques. In this thesis, a two-body ‘point absorber’ type wave energy converter with a mechanical power-takeoff is investigated. The two-body wave energy converter extracts energy through the relative motion of a floating buoy and a neutrally buoyant submerged body. Using a linear frequency-domain model, analytical solutions of the optimal power and the corresponding power-takeoff components are derived for the two-body wave energy converter. Using these solutions, a case study is conducted to investigate the influence of the submerged body size on the absorbed power of the device in regular and irregular waves. Here it is found that an optimal mass ratio between the submerged body and floating buoy exists where the device will achieve resonance. Furthermore, a case study to investigate the influence of the submerged body shape on the absorbed power is conducted using a time-domain numerical model. Here it is found that the submerged body should be designed to reduce the effects of drag, but to maintain relatively large hydrodynamic added mass and excitation force. To validate the analytical and numerical models, a 1/30th scale model of a two-body wave energy converter is tested in a wave tank. The results of the wave tank tests show that the two-body wave energy converter can absorb nearly twice the energy of a single-body ‘point absorber’ type wave energy converter.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Design, Optimization, and In-Depth Understanding of Front and Rear Junction Screen-Printed Double-Side Passivated Contacts Solar Cells

In this work, detailed numerical modeling is performed for front junction (FJ) and rear junction (RJ) n-type Si solar cells with screen-printed double-side poly-Si based tunnel oxide passivated contacts (TOPCon). Fundamental understanding of both structures is crucial to explore factors that limit the efficiency potential of the two designs. By investigating several key parameters such as front poly sheet resistance and thickness, bulk material properties, and carrier transport in our simulation model, we determine and explain why RJ cells outperform FJ cells. Our findings reveal that FJ suffers from present technological limitations of p-poly based passivated contacts, namely, i) large recombination observed in textured p-TOPCon emitter and ii) low solid solubility and hole mobility in boron-doped poly-Si resulting in very high sheet resistance of front p-poly layers which must be made thin to reduce absorption losses. In contrast, RJ desensitized the cell efficiency to front sheet resistance allowing application of ultra-thin front n-poly layers and is therefore ideally suited for double-side TOPCon cells. Lastly, we have developed a roadmap for efficiency projections of commercial-type screen-printed RJ and FJ topologies reaching ~24% and >22.5% efficiencies respectively, quantifying and explaining the impact of technological innovations on the performance of each design.

14 SOLAR ENERGY↗
DOE OSTI2017

Instrument design optimization with computational methods

Using Finite Element Analysis to approximate the solution of differential equations, two different instruments in experimental Hall C at the Thomas Jefferson National Accelerator Facility are analyzed. The time dependence of density uctuations from the liquid hydrogen (LH2) target used in the Q wea k experiment (2011-2012) are studied with Computational Fluid Dynamics (CFD) and the simulation results compared to data from the experiment. The 2.5 kW liquid hydrogen target was the highest power LH2 target in the world and the first to be designed with CFD at Jefferson Lab. The first complete magnetic field simulation of the Super High Momentum Spectrometer (SHMS) is presented with a focus on primary electron beam deflection downstream of the target. The SHMS consists of a superconducting horizontal bending magnet (HB) and three superconducting quadrupole magnets. The HB allows particles scattered at an angle of 5:5 deg to the beam line to be steered into the quadrupole magnets which make up the optics of the spectrometer. Without mitigation, remnant fields from the SHMS may steer the unscattered beam outside of the acceptable envelope on the beam dump and limit beam operations at small scattering angles. A solution is proposed using optimal placement of a minimal amount of shielding iron around the beam line.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

hashin_shtrikman_mp: a package for the optimal design and discovery of multi-phase composite materials

hashin_shtrikman_mp is a tool for composites designers who have desired composite properties in mind, but who do not yet have an underlying formulation. The library utilizes the tightest theoretical bounds on the effective properties of composite materials with unspecified microstructure – the Hashin-Shtrikman bounds – to identify candidate theoretical materials, find real materials that are close to the candidates, and determine the optimal volume fractions for each of the constituents in the resulting composite. Its features include (i) leveraging of materials in the Materials Project database, (ii) integration with the Materials Project API, (iii) use of genetic machine-learning, (iv) agnosticism to underlying microstructure, and (v) ultimate engineering application, make it a tool with much broader applications than its predecessors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Design, Optimization, and In-Depth Understanding of Front and Rear Junction Screen-Printed Double-Side Passivated Contacts Solar Cells

Investigate the efficiency potential of n-type screen-printed poly-Si based double-side tunnel oxide passivated contacts (DS-TOPCon) silicon solar cells Establish key material/device parameters and technologies to attain practically achievable DS-TOPCon cell efficiency by Quokka 2D Develop fundamental understanding of underlying mechanisms governing cell operation in front junction (FJ) and rear junction (RJ) cell designs to explain why RJ is a better choice for DS-TOPCon structure

14 SOLAR ENERGY↗
DOE OSTI2025

Design, Optimization, and Control of a 100 kW Electric Traction Motor Meeting or Exceeding DOE 2025 Targets

The overall objective of the electric motor portion of the Electric Drives Technology consortium is to research, develop, and test electric motors for use in electric vehicle applications capable of a peak power greater than 100 kW, power density greater than or equal to 50 kW/l, and a cost less than 3.3 $/kW. To meet the electric traction motor power density and cost targets a number of approaches were pursued simultaneously throughout the course of this project which address all of the major volumetric power density variables. The specific research thrusts at the Illinois Institute of Technology (IIT) are the following: multiphysics design for increased power density through maximum utilization of active materials, synthesis of electric machine windings and PM flux barriers with controlled space harmonics, high slot fill windings for increased current loadings or efficiency, aggressive cooling strategies, and design studies and prototype construction of candidate electric machines.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

System Modeling and Design Optimization for a Next-Generation Unattended Sensor

We are developing a next-generation unattendedsensor that can detect and identify radiation sources while operating on battery power for several weeks. The system achieves smaller size and weight over systems that use NaI:Tl and 3He detectors by using a relatively new scintillator, Cs2LiYCl6:Ce:Ce (CLYC). This material can detect both gamma rays and thermal neutrons, has energy resolution of ~4% full width at half maximum at 662 keV, and allows for particle discrimination by pulse amplitude as well as pulse shape. The overall design features an array of sixteen CLYC detectors, each read out by a photomultiplier tube and custom pulse processing electronics. A field-programmable gate array analyzes the energy spectra using computationally efficient algorithms for anomaly detection.

McDonald, Benjamin S.↗
DOE OSTI2022

Optimizing design and dispatch of a renewable energy system with combined heat and power

We embellish a mixed-integer program that prescribes a set of renewable energy, conventional generation, and storage technologies to procure, along with a corresponding dispatch strategy. Specifically, we add combined heat and power to this set. The model minimizes fixed and operational costs less incentives for the use of various technologies, subject to a series of component interoperability and system-wide constraints. The resulting mixed-integer linear program contains hundreds of thousands of variables and constraints. We demonstrate how to efficiently formulate and solve the corresponding instances such that we produce near-optimal solutions in minutes. A previous rendition of the model required hours of solution time for the same instances.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Refractive axicon for X-ray microscopy applications: design, optimization, and experiment

In a full-field transmission X-ray microscopy (TXM) setup, a condenser X-ray optical element is used to illuminate the sample by condensing the X-ray beam delivered by the synchrotron storage ring. On-going and future upgrades of synchrotron facilities to diffraction-limited storage rings will pose new challenges to these TXM setups, such as much smaller X-ray beams on the condenser. Here, we demonstrate that a refractive axicon can be used as an X-ray beam shaper to match the ring-shaped aperture of the condenser. Aiming at more efficient use of the incoming X-ray intensity, we explore several axicon designs both analytically and with numerical simulations. The axicons were produced by two-photon polymerization 3D printing on thin silicon nitride membrane substrates. The first characterization of the axicon was carried out at the TOMCAT beamline of the Swiss Light Source (Switzerland).

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Optimal Design of Intensified Towers for CO2 Capture with Internal, Printed Heat Exchangers

Solvent-based carbon capture processes typically suffer from the temperature rise of the solvent due to the heat of absorption of CO2. This increased temperature is not thermodynamically favor-able and results in a significant reduction in performance in the absorber column. As opposed to interstage coolers, which only remove, cool, and return the solvent at discrete locations in the column, internal coolers that are integrated with the packing can cool the process inline, which can result in improved efficiency. This work presents the modeling of these internal coolers within an existing generic, equation-oriented absorber column model that can cool the process while allowing for simultaneous mass transfer. Optimization of this model is also performed, which is capable of optimally choosing the best locations to place these devices, such that heat removal and mass transfer area are balanced. Results of the optimization have shown that optimally placed cooling elements result in a significant increase in the capture efficiency of the process, compared to a similar column with no internal cooling, with a common trend being the cooling of the column in the temperature bulge region. It is observed that by optimally placing an internal cooler, the solvent flow rate can be decreased, and the CO2 lean loading can be increased while still maintaining the same efficiency. These process changes can lead to a substantial reduction in costs due to lower reboiler duty.

Summits, Stephen↗