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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 397 records · Page 22

On-Demand Transit: Features, Benefits, Challenges, Costs, and Evaluation

The U.S. Department of Energy's National Laboratory of the Rockies works in partnership with communities and transit agencies across North America to support and evaluate customized on-demand transit (ODT) systems. ODT, also known as on-demand mobility or microtransit, is a flexible form of public mobility. Unlike traditional fixed-route transit, ODT adjusts where and when service is provided rather than following predetermined schedules and routes. Having evolved from commercial ride-hailing business models, ODT leverages smartphone connectivity and real-time route optimization to provide highly responsive and dynamic service. ODT trips, which are usually shared, can function as a standalone service or as a first-/last-mile service connecting riders to other types of transit.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Computationally Guided Development of Components for High Energy Density Solid-State Lithium-Sulfur Batteries

All electric vertical take-off and landing vehicles (eVTOL) for urban air mobility (UAM) concepts face numerous challenging technical barriers before their introduction into the consumer marketplace. The most challenging of these technical barriers to overcome is developing an energy storage system capable of meeting the rigorous aerospace safety and performance criteria1. The performance metrics for eVTOL craft, such as specific energy, specific power, and safety, exceed those of electric automobiles by a factor of two to four. Current state-of-the-art (SOA) lithium-ion batteries are incapable of meeting the key performance criteria of energy and safety for eVTOL. Therefore, next generation advanced chemistries and designs must be developed to meet required performance metrics for electric aviation2. Beyond lithium-ion chemistries, such as lithium-sulfur, show promise in their high energy, while limitations exist in their power and cyclability due to low electrical conductivity and high intermediate solubility in organic liquid electrolytes. Several strategies to overcome the low electrical conductivity involve the use of selenium as a dopant in the active sulfur material, along with the incorporation of 2-dimensional electron-conducting holey-graphene to improve the composite cathodes electronic conductivity. Furthermore, combining this chemistry with a solid-electrolyte avoids the components’ dissolution issues3. However, the development of composite solid-state cathodes is non-trivial as several components must be intimately mixed so that the active component has sufficient access to both electrons and lithium ions to undergo full electrochemical conversion. Mathematical modeling of battery components can assist experimental design through a robust and rigorous combination of computational modeling techniques covering multiple length scales. The objective is to leverage modern computational materials methods combined with battery multiphysics tools to develop radically advanced compatible cathode and electrolyte materials, build and test solid state lithium-sulfur cells and packs. A NASA-based cross-organizational team of high-powered experts combined integrated computational predictive modeling, fundamental chemistry analysis, advanced material science, and battery cell development to tackle this very challenging, multidisciplinary problem. This presentation will show a multiscale computational modeling approach that has produced a novel particle dynamics method called Solid Electrolyte Sphere Approximation Model (SESAM). SESAM modeling targets the 1-10 µm scale structures and provides electromechanical and grain interactions for predictive design guidelines for the manufacturing of solid-state components. Parameters such as particle size and volume fraction of the constituent materials were modeled and experimentally fabricated to optimize electrochemical performance through improved microstructure design. Experimental feedback was provided through ionic and electronic conductivity assessment and structural analysis of developed materials and cell components.

battery↗

Candidate Inorganic Photovoltaic Materials from Electronic Structure-Based Optical Absorption and Charge Transport Proxies

Approximately 33,000 valence-precise, ordered inorganic compounds tabulated in the Inorganic Crystal Structure Database have been screened for their potential as photovoltaic (PV) absorbers. This has been accomplished through the use of proxies for charge carrier mobilities and optical absorption properties from electronic structure calculations, in addition to constraints on thermodynamic stability. Preliminary screening of computed properties tabulated in the Materials Project Database, with subsequent high(er)-fidelity electronic structure calculations of optical properties and band gap corrections, indicates ≈200 known compounds on or near the convex hull which exhibit spectroscopic limited maximum efficiency (SLME) in excess of 25% for a 500 nm thin film, in addition to possessing low effective masses for both electrons and holes. Among the predicted high performers are nearly all the typical commercial inorganic thin-film PV materials and several previously unexplored candidates. The new candidates are drawn from a diverse set of chemical and structural families, including many chalcogenides and pnictides as well as antiperovskites, skutterudites, and semiconducting intermetallics. Here, carrier effective masses, SLME, corrected band gaps, and other relevant information for ≈800 compounds are made available for further analyses via the Materials Project MPContribs Framework.

14 SOLAR ENERGY↗

Advanced methods for preparation and characterization of infrared detector materials

Mercury cadmium telluride crystals were prepared by the Bridgman method with a wide range of crystal growth rates and temperature gradients adequate to prevent constitutional supercooling under diffusion-limited, steady state, growth conditions. The longitudinal compositional gradients for different growth conditions and alloy compositions were calculated and compared with experimental data to develop a quantitative model of the crystal growth kinetics for the Hg(i-x)CdxTe alloys, and measurements were performed to ascertain the effect of growth conditions on radial compositional gradients. The pseudobinary HgTe-CdTe constitutional phase diagram was determined by precision differential thermal analysis measurements and used to calculate the segregation coefficient of Cd as a function of x and interface temperature. Computer algorithms specific to Hg(1-x)CdxTe were developed for calculations of the charge carrier concentrations, charge carrier mobilities, Hall coefficient, optical absorptance, and Fermi energy as functions of x, temperature, ionized donor and acceptor concentrations, and neutral defect concentrations.

Lehoczky, S. L.↗

Mathematical models of continuous flow electrophoresis: Electrophoresis technology

Two aspects of continuous flow electrophoresis were studied: (1) the structure of the flow field in continuous flow devices; and (2) the electrokinetic properties of suspended particles relevant to electrophoretic separations. Mathematical models were developed to describe flow structure and stability, with particular emphasis on effects due to buoyancy. To describe the fractionation of an arbitrary particulate sample by continuous flow electrophoresis, a general mathematical model was constructed. In this model, chamber dimensions, field strength, buffer composition, and other design variables can be altered at will to study their effects on resolution and throughput. All these mathematical models were implemented on a digital computer and the codes are available for general use. Experimental and theoretical work with particulate samples probed how particle mobility is related to buffer composition. It was found that ions on the surface of small particles are mobile, contrary to the widely accepted view. This influences particle mobility and suspension conductivity. A novel technique was used to measure the mobility of particles in concentrated suspensions.

Saville, Dudley A.↗

NavP: Structured and Multithreaded Distributed Parallel Programming

We present Navigational Programming (NavP) -- a distributed parallel programming methodology based on the principles of migrating computations and multithreading. The four major steps of NavP are: (1) Distribute the data using the data communication pattern in a given algorithm; (2) Insert navigational commands for the computation to migrate and follow large-sized distributed data; (3) Cut the sequential migrating thread and construct a mobile pipeline; and (4) Loop back for refinement. NavP is significantly different from the current prevailing Message Passing (MP) approach. The advantages of NavP include: (1) NavP is structured distributed programming and it does not change the code structure of an original algorithm. This is in sharp contrast to MP as MP implementations in general do not resemble the original sequential code; (2) NavP implementations are always competitive with the best MPI implementations in terms of performance. Approaches such as DSM or HPF have failed to deliver satisfying performance as of today in contrast, even if they are relatively easy to use compared to MP; (3) NavP provides incremental parallelization, which is beyond the reach of MP; and (4) NavP is a unifying approach that allows us to exploit both fine- (multithreading on shared memory) and coarse- (pipelined tasks on distributed memory) grained parallelism. This is in contrast to the currently popular hybrid use of MP+OpenMP, which is known to be complex to use. We present experimental results that demonstrate the effectiveness of NavP.

navigational programming (NavP)↗

Evolutionary Computation for the Identification of Emergent Behavior in Autonomous Systems

Over the past several years the Center for Evolutionary Computation and Automated Design at the Jet Propulsion Laboratory has developed a technique based on Evolutionary Computational Methods (ECM) that allows for the automated optimization of complex computationally modeled systems. An important application of this technique is for the identification of emergent behaviors in autonomous systems. Mobility platforms such as rovers or airborne vehicles are now being designed with autonomous mission controllers that can find trajectories over a solution space that is larger than can reasonably be tested. It is critical to identify control behaviors that are not predicted and can have surprising results (both good and bad). These emergent behaviors need to be identified, characterized and either incorporated into or isolated from the acceptable range of control characteristics. We use cluster analysis of automatically retrieved solutions to identify isolated populations of solutions with divergent behaviors.

Terrile, Richard J.↗

The Multirotor Test Bed – A New NASA Test Capability for Advanced VTOL Rotorcraft Configurations

In November 2019, NASA completed the first wind tunnel test entry of the Multirotor Test Bed (MTB), a new test capability for advanced VTOL rotorcraft configurations. The MTB had been under development since 2017 when the need arose for an easily reconfigurable test stand for multirotor aircraft configurations. With the wide-ranging assortment of aircraft currently targeted at Urban Air Mobility and Unmanned Aircraft System applications, there is a need for validation data that will increase confidence in the computational modeling tools being used to develop these platforms. The MTB fills this need. This paper describes the key features of the MTB as well as its first wind tunnel test entry. A selection of results from the test is presented here, demonstrating the flexible configuration of the MTB and the types of data researchers can generate using this new test capability.

Multirotor Test Bed↗

A High-Performance Computing Predictive GNSS Performance Monitor for Autonomous Air Vehicles in Urban Environments

This report offers analysis and design insights for leveraging High-Performance Computing (HPC) to predict line-of-sight (LOS) Global Navigation Satellite System (GNSS) availability in a city. This work is motivated by the emerging fields of Advanced and Urban Air Mobility (AAM/UAM), where regulatory authorities are seeking city-scale, meter-resolution risk forecasting in order to safely integrate new flight missions with existing urban life and infrastructure. This work addresses the technical challenge of efficiently computing urban GNSS satellite visibility to predict GNSS performance metrics under these requirements. We present a new HPC-optimized shadow casting algorithm variant as a ray-based approach to forecasting satellite visibility. We apply this algorithm variant in a software-defined prognostic service which generates a GNSS navigation risk-correlated map as a path planning-style potential field. We detail dominant computational burdens, viable simplifying assumptions, and different algorithmic implementations, intending to demonstrate a baseline of computation time needed by each stage in such a service. We conclude by analyzing the prototype service’s prediction accuracy compared to receiver data from Corpus Christi, Texas. This informs design trade-offs along the dimensions of hardware, computation time, and tolerable forecasting error (including proportions of false positives and false negatives).

GNSS↗

Atomic Diffusion, Segregation, and Grain Boundary Migration in Nickel-Based Alloys from Molecular Dynamics Simulations

Grain boundary diffusion and metal mobility in alloys control material performance in many applications and yet remain poorly understood at a mechanistic level. With advances in accessible time and length scales for computational molecular simulations, and recent force field developments, we now possess tools to help unravel those mechanisms. Using large-scale molecular dynamics simulations, here we examined vacancy-mediated diffusion processes in Ni-5Cr alloy with low and high-energy grain boundaries. We show that atomic diffusion inside the grain boundary plane is about four times higher than bulk diffusion, at any temperature, and exhibits a typical Arrhenius behavior with a very small energy barrier (0~.8 eV for Cr and 0.7 eV for Ni within 1300-1600 K). Additionally, the fastest diffusing species inverts; Cr diffusion was faster than Ni in the bulk but slower in the grain boundaries. This is attributed to the creation of high cohesive energy clusters of Cr at the grain boundary. Grain boundary migration was also observed to be temperature dependent and appears to be two times higher in the 5% Cr alloy than in pure Ni, highlighting the important role of the alloying element on grain boundary motion.

Simonnin, Pauline GN↗

Evaluating Material Design Principles for Calcium-Ion Mobility in Intercalation Cathodes

Multivalent-ion batteries offer an alternative to Li-based technologies, with the potential for greater sustainability, improved safety, and higher energy density, primarily due to their rechargeable system featuring a passivating metal anode. Although a system based on the Ca 2+ /Ca couple is particularly attractive given the low electrochemical plating potential of Ca 2+ , the remaining challenge for a viable rechargeable Ca battery is to identify Ca cathodes with fast ion transport. In this work, a high-throughput computational pipeline is adapted to (1) discover novel Ca cathodes in a largely unexplored space of empty intercalation hosts and (2) develop material design rules for Ca-ion mobility. One candidate from the screening, W 2 O 3 (PO 4 ) 2 , is confirmed to have a low Nudged Elastic Band (NEB) barrier of 168 meV within a one-dimensional (1D) ion percolation topology. This candidate is subsequently synthesized and electrochemically tested, achieving reversible Ca cycling with a capacity of 25 mA h/g. To further accelerate the screening for promising Ca intercalation electrodes, machine learning (ML) Random Forest (RF) and Extreme Gradient Boosting (XGB) classification models are created with local environment descriptors based on a large, structurally and chemically diverse dataset of minimum energy pathways, spanning over 5,000 density functional theory (DFT) site energy calculations. Accuracies of 92% are achieved, material design metrics are quantified, ML force-fields are leveraged in an accelerated iteration of the screening, and a total of 27 novel Ca cathode materials are highlighted for further investigation.

25 ENERGY STORAGE↗

Numerical Investigation of a Small Low-Flow Marine Hydrokinetic (MHK) Turbine for Small Autonomous Unmanned Mobile Recharge Stations (CRADA Final Report)

This project will improve the hydrodynamic performance of the undershot waterwheel turbine with a flow concentrator designed by the Participant, using a computational fluid dynamics study. The influence of different result parameters including the number of blades, turbine profile, submerged depth, tip speed ratio, concentrator geometry and wave + current conditions will be assessed to maximize power performance and minimize structural loads.

16 TIDAL AND WAVE POWER↗

Trellis coding with Continuous Phase Modulation (CPM) for satellite-based land-mobile communications

This volume of the final report summarizes the results of our studies on the satellite-based mobile communications project. It includes: a detailed analysis, design, and simulations of trellis coded, full/partial response CPM signals with/without interleaving over various Rician fading channels; analysis and simulation of computational cutoff rates for coherent, noncoherent, and differential detection of CPM signals; optimization of the complete transmission system; analysis and simulation of power spectrum of the CPM signals; design and development of a class of Doppler frequency shift estimators; design and development of a symbol timing recovery circuit; and breadboard implementation of the transmission system. Studies prove the suitability of the CPM system for mobile communications.

Source record↗

Planned LMSS propagation experiment using ACTS: Preliminary antenna pointing results during mobile operations

An overview and a status description of the planned LMSS mobile K band experiment with ACTS is presented. As a precursor to the ACTS mobile measurements at 20.185 GHz, measurements at 19.77 GHz employing the Olympus satellite were originally planned. However, because of the demise of Olympus in June of 1991, the efforts described here are focused towards the ACTS measurements. In particular, we describe the design and testing results of a gyro controlled mobile-antenna pointing system. Preliminary pointing measurements during mobile operations indicate that the present system is suitable for measurements employing a 15 cm aperture (beamwidth at approximately 7 deg) receiving antenna operating with ACTS in the high gain transponder mode. This should enable measurements with pattern losses smaller than plus or minus 1 dB over more than 95 percent of the driving distance. Measurements with the present mount system employing a 60 cm aperture (beamwidth at approximately 1.7 deg) results in pattern losses smaller than plus or minus 3 dB for 70 percent of the driving distance. Acceptable propagation measurements may still be made with this system by employing developed software to flag out bad data points due to extreme pointing errors. The receiver system including associated computer control software has been designed and assembled. Plans are underway to integrate the antenna mount with the receiver on the University of Texas mobile receiving van and repeat the pointing tests on highways employing a recently designed radome system.

Rowland, John R.↗

Architecture-Aware Models of AI Engines for High-Performance Matrix Matrix Multiplication

The AI Engine (AIE) architecture, available in systems from mobile SoCs to server-class FPGAs, aims to efficiently execute AI/ML tasks through a two-dimensional array of compute tiles. Previous work on AIEs has explored different approaches to mapping computation across spatial arrays, but the compute kernel running on each tile has not been the focus. Additionally, the AIE-ML architecture introduces memory tiles and omits programmable logic, requiring new approaches to staging and moving data throughout the array. In this work we update analytical models developed for CPUs to produce the design of high performance kernels while introducing new model considerations such as memory structure, throughput, and latency as required by the AIE hardware. We evaluate our models by developing AIE-ML kernels for matrix multiplication in low-precision data types showing performance up to 95% of compute peak for the kernel when data resides in local memory and above 90% of compute peak when data resides in main memory.

Binder, Elliott D. [Carnegie Mellon University, Pi↗

Software for Digital Acquisition System and Application to Environmental Monitoring

Criteria for selection of a minicomputer for use as a core resident acquisition system were developed for the ODU Mobile Air Pollution Laboratory. A comprehensive data acquisition program named MONARCH was instituted in a DEC-8/E-8K 12-bit computer. Up to 32 analog voltage inputs are scanned sequentially, converted to BCD, and then to actual numbers. As many as 16 external devices (valves or any other two-state device) are controlled independently. MONARCH is written as a foreground-background program, controlled by an external clock which interrupts once per minute. Transducer voltages are averaged over user specified time intervals and, upon completion of any desired time sequence, outputted are: day, hour, minute, second; state of external valves; average value of each analogue voltage (E Format); as well as standard deviations of these values. Output is compatible with any serially addressed media.

Copeland, G. E.↗

Dynamic Modeling and Soil Mechanics for Path Planning of the Mars Exploration Rovers

To help minimize risk of high sinkage and slippage during drives and to better understand soil properties and rover terramechanics from drive data, a multidisciplinary team was formed under the Mars Exploration Rover project to develop and utilize dynamic computer-based models for rover drives over realistic terrains. The resulting system, named ARTEMIS (Adams-based Rover Terramechanics and Mobility Interaction System), consists of the dynamic model, a library of terramechanics subroutines, and the high-resolution digital elevation maps of the Mars surface. A 200-element model of the rovers was developed and validated for drop tests before launch, using Adams dynamic modeling software. The external library was built in Fortran and called by Adams to model the wheel-soil interactions include the rut-formation effect of deformable soils, lateral and longitudinal forces, bull-dozing effects, and applied wheel torque. The paper presents the details and implementation of the system. To validate the developed system, one study case is presented from a realistic drive on Mars of the Opportunity rover. The simulation results match well from the measurement of on-board telemetry data. In its final form, ARTEMIS will be used in a predictive manner to assess terrain navigability and will become part of the overall effort in path planning and navigation for both Martian and lunar rovers.

rover↗