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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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NASA NTRS2021

Dealing with Ion LET Uncertainties: An Application of Generalized Linear Models

Although most SEE rate estimation methods presume a fit to SEE cross section vs. LET, fitting SEE data is challenging because the data are not compatible with the assumptions of many common fitting techniques (e.g. linear regression. The difficulty of fitting such data is compounded when the LET of the ion responsible for an SEE is uncertain. We modify a Generalized Linear Model SEE data fitting methodology to accommodate uncertain LET and apply the method to the problem of backside heavy-ion SEE testing to demonstrate the utility of the method, explore the dependence of systematic errors that arise from improper treatment of LET uncertainty and develop guidelines for minimizing such systematic errors when proper treatment is not possible. Additional applications are suggested and assessed for suitability of treatment by the model.

Single-event effects↗
NASA NTRS2019

Enhancing Battery Safety with Fractional Thermal Runaway Calorimetry

Effective thermal management systems, designed to handle the impacts of thermal runaway (TR) and to prevent cell-to-cell propagation, are key to safe operation of lithium-ion (Li-ion) battery assemblies. Critical factors for optimising these systems include the total energy released during a single cell TR event and the fraction of the total energy that is released through the cell casing versus through the ejecta material. A unique fractional thermal runaway calorimeter (FTRC), designed to characterise said critical factors, was utilised to examine the TR behaviour of Li-ion cells). Delegates will be provided with an in-depth discussion on what fractional thermal runaway calorimetry is and how it benefits the development of safe and optimised battery assemblies that protect against thermal runaway. Delegates will see calorimetry data associated with a variety of Li-ion cells. Data presented is relevant to any industry that utilises high-energy Li-ion cells in closed environments and has a need to focus on safety.

Walker, William↗
NASA NTRS2004

Tradeoffs in Flight Design Upset Mitigation in State of the Art FPGAs: Hardened by Design vs. Design Level Hardening

This presentation compares and contrasts the effectiveness and the system/designer impacts of the two main approaches to upset hardening: the Actel approach (RTSX-S and RTAX-S) of low-level (inside each flip-flop) triplication and the Xilinx approach (Virtex and Virtex2) of design-level triplication of both functional blocks and voters. The effectiveness of these approaches is compared using measurements made in conjunction with each of the FPGAs' manufacturer: for Actel, published data [1] and for Xilinx, recent results from the Xilinx SEE Test Consortium (note that the author is an active and founding member). The impacts involve Actel advantages in the areas of transistor-utilization efficiency and minimizing designer involvement in the triplication while the Xilinx advantages relate to the ability to custom tailor upset hardness and the flexibility of re-configurability. Additionally, there are currently clear Xilinx advantages in available features such as the number of I/O's, logic cells, and RAM blocks as well as speed. However, the advantage of the Actel anti-fuses for configuration over the Xilinx SRAM cells is that the latter need additional functionality and external circuitry (PROMs and, at least a watchdog timer) for configuration and configuration scrubbing. Further, although effectively mitigated if done correctly, the proton upset-ability of the Xilinx FPGAs is a concern in severe proton-rich environments. Ultimately, both manufacturers' upset hardening is limited by SEFI (single-event functional interrupt) rates where it appears the Actel results are better although the Xilinx Virtex2-family result of about one SEFI in 65 device-years in solar-min GCR (the more intense part of the galactic cosmic-ray background) should be acceptable to most missions

radiation effects↗
NASA NTRS2023

Safety Case for Small Uncrewed Aircraft Systems (sUAS) Beyond Visual Line of Sight (BVLOS) Operations at NASA Langley Research Center

This Technical Memorandum (TM) is written to provide for dissemination of the methods and safety considerations for operations of small Uncrewed Aerial Systems (sUAS) Beyond Visual Line-of-Sight (BVLOS)at NASA Langley Research Center. It includes the Safety Case used to acquire a BVLOS Certificate of Authorization (COA) from the FAA and is being published to enable others to benefit from this work. The intended operations, subject to approval from the Federal Aviation Administration (FAA) and the National Aeronautics and Space Administration (NASA), will include a combination of Within Visual Line of Sight (WVLOS) and Beyond Visual Line of Sight (BVLOS) flights, comprising of at most five sUAS operating concurrently, with no more than three operating BVLOS. Flights will occur in a subset of the Langley Air Force Base (LAFB) Class D airspace (KLFI) at a maximum altitude of 400 ft AGL. Most operations within this subset will take place in the City Environment Range Testing for Autonomous Integrated Navigation (CERTAIN) Range. The CERTAIN Range includes airspace inside the borders of NASA Langley Research Center (LaRC). Additional airspace over the northern section of CERTAIN will be requested as part of the Certificate of Authorization (COA). NASA LaRC BVLOS operations on the CERTAIN Range can be broken down into five critical components needed to meet the 14 CFR § 91.113 see and avoid requirement: 1) procedural deconfliction with LAFB for UAS operations at or below 400 ft and manned aircraft at or above 900’ AGL; 2) ground equipment for detection of intruder aircraft and to support communications between crewmembers ; 3) sUAS vehicles with advanced onboard automation capable of autonomously maintaining safe separation; 4) BVLOS standardized operating procedures (SOPs); 5) and personnel to execute the flight operations in accordance with the SOPs and respond to airborne contingencies. The introduction of new ground equipment includes the use of the Remote Operations for Autonomous Missions (ROAM) UAS Operations Center, development and use of an Integrated Airspace Display (IAD), use of the L-STAR and GA-9120 radars, and the incorporation of standardized Vertiports. The ROAM Operations Center will be the central point for all BVLOS sUAS operations. All command and control (C2), voice communications and airspace awareness displays will reside inside ROAM. The IAD will provide raw data from ADS-B, FLARM, radar tracks and telemetered GPS vehicle positions for interpretation by an Airspace Monitor. The radars will search the class D airspace around the CERTAIN Range and serve as a backup to procedural deconfliction procedures coordinated with LAFB. In the event of a procedural deconfliction breakdown, radar detections of non-participating aircraft will be available so that the 91.113 see and avoid requirement can still be safely met. Finally, the incorporation of Vertiports will have video and network connectivity that enables large numbers of sUAS launches and recoveries from a single location. This is a continuation of the remote command and control of unpiloted aircraft component focused on evaluating unpiloted aircraft flight crew roles and responsibilities, control interfaces and the associated data links needed to operate a fleet of aircraft within a UAM Ecosystem. This work supports the development of future aviation operational concepts based on an Urban Air Mobility Maturity Level (UML) 4 environment (Patterson, 2020). It is assumed that future airspace will include hundreds of simultaneous aircraft operations within the airspace, therefore scalable operations are essential for enabling this future airspace to become a reality. Follow on work includes envisioned flights that expand operations beyond the CERTAIN range and lead to an effective Maritime Surveillance capability.

Matthew W Coldsnow↗
NASA NTRS2004

FPGA-Based, Self-Checking, Fault-Tolerant Computers

A proposed computer architecture would exploit the capabilities of commercially available field-programmable gate arrays (FPGAs) to enable computers to detect and recover from bit errors. The main purpose of the proposed architecture is to enable fault-tolerant computing in the presence of single-event upsets (SEUs). [An SEU is a spurious bit flip (also called a soft error) caused by a single impact of ionizing radiation.] The architecture would also enable recovery from some soft errors caused by electrical transients and, to some extent, from intermittent and permanent (hard) errors caused by aging of electronic components. A typical FPGA of the current generation contains one or more complete processor cores, memories, and highspeed serial input/output (I/O) channels, making it possible to shrink a board-level processor node to a single integrated-circuit chip. Custom, highly efficient microcontrollers, general-purpose computers, custom I/O processors, and signal processors can be rapidly and efficiently implemented by use of FPGAs. Unfortunately, FPGAs are susceptible to SEUs. Prior efforts to mitigate the effects of SEUs have yielded solutions that degrade performance of the system and require support from external hardware and software. In comparison with other fault-tolerant- computing architectures (e.g., triple modular redundancy), the proposed architecture could be implemented with less circuitry and lower power demand. Moreover, the fault-tolerant computing functions would require only minimal support from circuitry outside the central processing units (CPUs) of computers, would not require any software support, and would be largely transparent to software and to other computer hardware. There would be two types of modules: a self-checking processor module and a memory system (see figure). The self-checking processor module would be implemented on a single FPGA and would be capable of detecting its own internal errors. It would contain two CPUs executing identical programs in lock step, with comparison of their outputs to detect errors. It would also contain various cache local memory circuits, communication circuits, and configurable special-purpose processors that would use self-checking checkers. (The basic principle of the self-checking checker method is to utilize logic circuitry that generates error signals whenever there is an error in either the checker or the circuit being checked.) The memory system would comprise a main memory and a hardware-controlled check-pointing system (CPS) based on a buffer memory denoted the recovery cache. The main memory would contain random-access memory (RAM) chips and FPGAs that would, in addition to everything else, implement double-error-detecting and single-error-correcting memory functions to enable recovery from single-bit errors.

Some, Raphael↗
NASA NTRS2006

Submicrosecond Power-Switching Test Circuit

A circuit that changes an electrical load in a switching time shorter than 0.3 microsecond has been devised. This circuit can be used in testing the regulation characteristics of power-supply circuits . especially switching power-converter circuits that are supposed to be able to provide acceptably high degrees of regulation in response to rapid load transients. The combination of this power-switching circuit and a known passive constant load could be an attractive alternative to a typical commercially available load-bank circuit that can be made to operate in nominal constant-voltage, constant-current, and constant-resistance modes. The switching provided by a typical commercial load-bank circuit in the constant-resistance mode is not fast enough for testing of regulation in response to load transients. Moreover, some test engineers do not trust the test results obtained when using commercial load-bank circuits because the dynamic responses of those circuits are, variously, partly unknown and/or excessively complex. In contrast, the combination of this circuit and a passive constant load offers both rapid switching and known (or at least better known) load dynamics. The power-switching circuit (see figure) includes a signal-input section, a wide-hysteresis Schmitt trigger that prevents false triggering in the event of switch-contact bounce, a dual-bipolar-transistor power stage that drives the gate of a metal oxide semiconductor field-effect transistor (MOSFET), and the MOSFET, which is the output device that performs the switching of the load. The MOSFET in the specific version of the circuit shown in the figure is rated to stand off a potential of 100 V in the "off" state and to pass a current of 20 A in the "on" state. The switching time of this circuit (the characteristic time of rise or fall of the potential at the drain of the MOSFET) is .300 ns. The circuit can accept any of three control inputs . which one depending on the test that one seeks to perform: a repetitive waveform from a signal generator, momentary closure of a push-button switch, or closure or opening of a manually operated on/off switch. In the case of a signal generator, one can adjust the frequency and duty cycle as needed to obtain the desired AC power-supply response, which one could display on an oscilloscope. Momentary switch closure could be useful for obtaining (and, if desired, displaying on an oscilloscope set to trigger on an event) the response of a power supply to a single load transient. The on/off switch can be used to switch between load states in which static-load regulation measurements are performed.

Folk, Eric N.↗
NASA NTRSDate not supplied

The INSTEP Monitoring Network: Merging High-and-Low Cost Measurements to Characterize California Wildfires

Despite challenges with data quality and scope, low-cost sensor networks have skyrocketed in popularity over the last 15 years, making air quality data available on refined spatial scales. More recently, studies have leveraged both high and low-quality instruments to create stronger “hybrid” models, with most studies focusing on particulate matter. Low-cost measurements typically represent ground-level emissions only, providing context for human health issues from climate change-driven events such as wildfires. Since low-cost sensors’ capabilities are localized, daily events and microclimates tend to dominate the data rather than larger regional or atmospheric trends. Likewise, their low cost explains their high uncertainty. In contrast, some regulatory-grade instruments produce column measurements as well, providing reliable information on a broader scope. To bridge this gap while expanding into gas-phase measurements, we deployed 12 air quality sensor packages in California, USA during the 2022 wildfire season. These INSTEP (Inexpensive Network Sensor Technology Exploring Pollution) monitors measure carbon monoxide (CO), carbon dioxide (CO2), ozone (O3), nitrogen dioxide (NO2), and several hydrocarbons including methane (CH4) and formaldehyde (HCHO). Half of the monitors were co-located with remote sensing spectrometers: NASA Pandora and Total Column Carbon Observing Network (TCCON). The overlap in pollutants includes NO2, O3, and HCHO between the INSTEP monitors and the Pandora column measurements. TCCON covers column CO, CO2, and CH4, rounding out our comparison. Most of the monitors were distributed throughout the San Francisco Bay area, and an additional three were located within 100 km of Los Angeles. The sites ranged in geographic and population characteristics, including desert, mountainous, coastal, and urban locations. Since varying environmental conditions such as temperature and pressure are known to challenge sensor performance, we will apply newer sensor “calibration” techniques meant to combat this. We will normalize our sensor signals by z-scoring them prior to applying a single calibration model in the form of multivariate linear regression or an artificial neural network. While this technique has been validated for the hydrocarbon and ozone sensor types (metal oxide), it has not yet been tested on electrochemical and non-dispersive infrared sensors, which are also used in the INSTEP monitors. This will serve as a test to see if this normalization technique – or another – is most effective in accounting for environmental differences among sensors. Related data analysis efforts have found success with a variety of geospatial analysis techniques, including weighted network models in which high-quality instruments are given higher weights than their low-cost counterparts. Our preliminary analysis will focus on kriging, which uses a Gaussian algorithm to assign weights, providing estimated pollution levels at locations between monitors. Smoke trajectory and evolution will also be considered using both measurement types. We also aim to baseline subtract our emission estimates from each region to determine which portion of emissions are regional and local, further characterizing burn differences in northern and southern California fires. Future directions include using INSTEP jointly with TEMPO satellite data, and mobile deployments on aircraft and uncrewed aerial vehicles (UAV).

Low-cost sensors↗
NASA NTRSDate not supplied

Robustness of Semi-Superjunction 4H-SiC Power DMOSFETs to Single-Event Burnout from Heavy Ion Bombardment

We compare the failure mechanism and performance of a silicon carbide (SiC) semi-superjunction (semi-SJ) power DMOSFET against pure SJ and conventional DMOSFET when struck by a single heavy ion. The Single-Event Burnout (SEB) failure mechanism was identified as the thermal runaway from second breakdown resulting in mesoplasma formation. The semi-SJ design shifts the mesoplasma location from the drift/substrate interface seen in the control device structures to a location along the center of the P-pillar and closer towards the DMOSFET surface, thus significantly improving the SEB threshold voltage. The SEB threshold voltage varies with pillar width and ratio of pillar thickness to drift layer thickness. A maximum value of SEB threshold voltage is reached when the pillar to drift layer ratio is 0.9 and the pillar width is 2.4 μm. The semi-SJ SEB/breakdown voltage ratio is 100% and 13% higher than the pure SJ and conventional DMOSFET, respectively. Using a new figure of merit (FOM), which accounts for the tradeoff between SEB threshold voltage and on-state performance, we find that the SiC semi-SJ DMOSFET achieves a FOM that is 1.8 and 8 times higher than SJ and conventional DMOSFET, respectively, making the semi-SJ a competitive candidate for radiation hardened applications.

SiC↗
NASA NTRS2009

Forecasting Lightning Threat using Cloud-resolving Model Simulations

As numerical forecasts capable of resolving individual convective clouds become more common, it is of interest to see if quantitative forecasts of lightning flash rate density are possible, based on fields computed by the numerical model. Previous observational research has shown robust relationships between observed lightning flash rates and inferred updraft and large precipitation ice fields in the mixed phase regions of storms, and that these relationships might allow simulated fields to serve as proxies for lightning flash rate density. It is shown in this paper that two simple proxy fields do indeed provide reasonable and cost-effective bases for creating time-evolving maps of predicted lightning flash rate density, judging from a series of diverse simulation case study events in North Alabama for which Lightning Mapping Array data provide ground truth. One method is based on the product of upward velocity and the mixing ratio of precipitating ice hydrometeors, modeled as graupel only, in the mixed phase region of storms at the -15\dgc\ level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domainwide statistics of the peak values of simulated flash rate proxy fields against domainwide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. A blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Weather Research and Forecast Model simulations of selected North Alabama cases show that this model can distinguish the general character and intensity of most convective events, and that the proposed methods show promise as a means of generating quantitatively realistic fields of lightning threat. However, because models tend to have more difficulty in correctly predicting the instantaneous placement of storms, forecasts of the detailed location of the lightning threat based on single simulations can be in error. Although these model shortcomings presently limit the precision of lightning threat forecasts from individual runs of current generation models, the techniques proposed herein should continue to be applicable as newer and more accurate physically-based model versions, physical parameterizations, initialization techniques and ensembles of cloud-allowing forecasts become available.

McCaul, E. W., Jr.↗
NASA NTRS2004

The NASA Continuous Risk Management Process

As an intern this summer in the GRC Risk Management Office, I have become familiar with the NASA Continuous Risk Management Process. In this process, risk is considered in terms of the probability that an undesired event will occur and the impact of the event, should it occur (ref., NASA-NPG: 7120.5). Risk management belongs in every part of every project and should be ongoing from start to finish. Another key point is that a risk is not a problem until it has happened. With that in mind, there is a six step cycle for continuous risk management that prevents risks from becoming problems. The steps are: identify, analyze, plan, track, control, and communicate & document. Incorporated in the first step are several methods to identify risks such as brainstorming and using lessons learned. Once a risk is identified, a risk statement is made on a risk information sheet consisting of a single condition and one or more consequences. There can also be a context section where the risk is explained in more detail. Additionally there are three main goals of analyzing a risk, which are evaluate, classify, and prioritize. Here is where a value is given to the attributes of a risk &e., probability, impact, and timeframe) based on a multi-level classification system (e.g., low, medium, high). It is important to keep in mind that the definitions of these levels are probably different for each project. Furthermore the risks can be combined into groups. Then, the risks are prioritized to see what risk is necessary to mitigate first. After the risks are analyzed, a plan is made to mitigate as many risks as feasible. Each risk should be assigned to someone in the project with knowledge in the area of the risk. Then the possible approaches to choose from are: research, accept, watch, or mitigate. Next, all risks, mitigated or not, are tracked either individually or in groups. As the plan is executed, risks are re-evaluated, and the attribute values are adjusted as necessary. Metrics are established and monitored as tools for risk tracking. Also a trigger or threshold should be set on the metric data that indicates when an action is needed. Results of this tracking are usually evaluated and reported in a relevant format at weekly or monthly meetings. Choosing controls is the subsequent step, which involves the effects of the tracking. The three basic controls are: close, continue tracking, and re- plan. Finally communicate & document is the last step, but occurs throughout the process. It is vital that main risks, plans, changes, and progress are known by everyone in the project. A good way to keep everyone updated and inform other projects of common issues is by thoroughly documenting project risks. NASA sees value in risk management and believes that projects have greater probability or success by using the NASA Continuous Risk Management Process.

Pokorny, Frank M.↗
DOE OSTI2020

Study of the Mu2e sensitivity to the $\mu^-\rightarrow e^+$ conversion process

The Mu2e experiment at Fermilab (Batavia, IL) will search for the coherent neutrinoless conversion of a muon into an electron in the electric field of an aluminum atom. The conversion process results in a monochromatic electron with energy slightly below the muon rest mass ($E_e= 104.97$ MeV). The experiment goal is to improve the previous measurement by four orders of magnitude and reach a single event sensitivity of $3 \times 10^{-17} $ on the conversion rate with respect to the muon capture rate. \\ The experiment will deliver a very intense pulsed negative muon beam to an aluminum target to achieve a total number of $10^{18}$ stopped muons in three years of running. Production and transport of the muons are accomplished with a sophisticated magnetic system comprised of a Production, a Transport and a Detector solenoid, with the last one hosting a Straw-tube Tracker and a Crystal Calorimeter. The entire detector region is surrounded by a Cosmic Ray Veto system. Mu2e is und er construction at the Muon Campus of Fermilab. \\ The INFN italian group is responsible for the design and construction of the crystal calorimeter, which plays a crucial role in the Mu2e measurement, providing particle identification capabilities fundamental for the rejection of the different background sources that can mimic a conversion electron. The calorimeter information allows also to improve the tracking performances it provides a fast standalone trigger for the experiment.\\ After a long R\&D phase, the final drawings see a calorimeter comprised of 1348 pure CsI crystals arranged in two annular disks. Each crystal is readout by two custom UV-extended Silicon Photomultipliers (SiPMs). Performances of the selected components were verified with an electron beam test, carried out in 2017 at the Beam Test Facility (BTF) at the National Laboratories of Frascati, on a large size prototype of 51 crystals and 102 SiPMs, confirming excellent energy ($\sigma_{E}/E = \mathcal{O }(10\%)$) and timing ($\sigma_{T} <500$ ps) resolutions in a! greement with the Mu2e specifications.\\ In the first chapters of this thesis, I describe my involvement in the calorimeter activities, with particular emphasis on the data analysis of the prototype energy response and resolution, that I was personally leading. Moreover, a description of the tuning of the simulation and the careful data-MC comparison is also reported.\\ An auxiliary measurement that can be performed with Mu2e is the search for a Lepton Number Violation (LNV) process where the negatively charged muon converts, without neutrinos, into a positron, $\mu ^{-} +N(A,Z) \rightarrow $ e$^+ +N(A,Z-2)$. At the moment of writing, Neutrinoless Double Beta Decay (0$\nu \beta \beta$) has set the most stringent limit on the LNV processes (T$^{0\nu \beta \beta}_{1/2} > 1.1 \times 10^{26} $ yr at 90$\%$ CL) with the GERDA experiment. In 0$\nu \beta \beta$ a pair of free electrons is created in the transformation from a nucleus $(A, Z)$ into its daughter $(A, Z + 2)$, namely: $(A,Z)\rightarrow (A, Z+2) =2 e^-$. Similar transitions could proceed through the emission of a pair of positrons, double electron capture (EC), or EC and single emission of a positron, with the nucleus changing from $(A, Z)$ to $(A, Z - 2)$. All these variations are equally interesting when discussing of new Physics, since they all manifest a non-conservation of the number of leptons.\\ Moreover, recent studies show that, because of flavor effect, off-diagonal processes, such as the $\mu^- -e^+$ conversion, can have their rate enhanced with respect to processes occurring in the $e-e$ sector.\\ Mu2e will search for $\mu^- + Al(27,13) \rightarrow e^+ +Na(27,11)$, only considering ground state transition, producing a conversion positron with energy $E_{e^+}= 92.32 $ MeV.\\ This thesis is focused on this search. In particular, I developed an algorithm to account for the radiative corrections to be applied to the conversion positrons that resulted in a few percent reduction in s ignal acceptance.\\ One of the most prominent background to ! this sear! ch is the Radiative Muon Capture (RMC) $ \mu+ N(Z,A)\rightarrow \gamma + \nu_{\mu} + N(Z-1,A)$. The produced photon can convert, virtually or in the detector materials (in the following referred as internal or external conversion respectively) in an electron-positron pair, producing positrons with energies approaching the expected conversion energy. Experimental results from previous experiments indicate the RMC endpoint ($\kmax$) to be of $\sim$ 90 MeV. A precise modeling of this background is relevant due to the proximity of the photon spectrum endpoint to the positron conversion energy. The calorimeter group is obviously interested to reconstruct the RMC distribution having also the opportunity to improve the current knowledge of the process. \\ A toy MC has been developed to evaluate the number of $e^+$ from external RMC background in the signal window. Knowing this value and ev...

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗