Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “State Level Concept”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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

At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Impact of Probabilistic Weather on Flight Routing Decisions

Flight delays in the United States have been found to increase year after year, along with the increase in air traffic. During the four-month period from May through August of 2005, weather related delays accounted for roughly 70% of all reported delays, The current weather prediction in tactical (within 2 hours) timeframe is at manageable levels, however, the state of forecasting weather for strategic (2-6 hours) timeframe is still not dependable for long-term planning. In the absence of reliable severe weather forecasts, the decision-making for flights longer than two hours is challenging. This paper deals with an approach of using probabilistic weather prediction for Traffic Flow Management use, and a general method using this prediction for estimating expected values of flight length and delays in the National Airspace System (NAS). The current state-of-the-art convective weather forecasting is employed to aid the decision makers in arriving at decisions for traffic flow and flight planing. The six-agency effort working on the Next Generation Air Transportation System (NGATS) have considered weather-assimilated decision-making as one of the principal foci out of a list of eight. The weather Integrated Product Team has considered integrated weather information and improved aviation weather forecasts as two of the main efforts (Ref. 1, 2). Recently, research has focused on the concept of operations for strategic traffic flow management (Ref. 3) and how weather data can be integrated for improved decision-making for efficient traffic management initiatives (Ref. 4, 5). An overview of the weather data needs and benefits of various participants in the air traffic system along with available products can be found in Ref. 6. Previous work related to use of weather data in identifying and categorizing pilot intrusions into severe weather regions (Ref. 7, 8) has demonstrated a need for better forecasting in the strategic planning timeframes and moving towards a probabilistic description of weather (Ref. 9). This paper focuses on. specified probability in a local region for flight intrusion/deviation decision-making. The process uses a probabilistic weather description, implements that in a air traffic assessment system to study trajectories of aircraft crossing a cut-off probability contour. This value would be useful for meteorologists in creating optimum distribution profiles for severe weather, Once available, the expected values of flight path and aggregate delays are calculated for efficient operations. The current research, however, does not deal with the issue of multiple cell encounters, as well as echo tops, and will be a topic of future work.

Sheth, Kapil↗
DOE OSTI2024

Integrated edge-to-exascale workflow for real-time steering in neutron scattering experiments

We introduce a computational framework that integrates artificial intelligence (AI), machine learning, and high-performance computing to enable real-time steering of neutron scattering experiments using an edge-to-exascale workflow. Focusing on time-of-flight neutron event data at the Spallation Neutron Source, our approach combines temporal processing of four-dimensional neutron event data with predictive modeling for multidimensional crystallography. At the core of this workflow is the Temporal Fusion Transformer model, which provides voxel-level precision in predicting 3D neutron scattering patterns. The system incorporates edge computing for rapid data preprocessing and exascale computing via the Frontier supercomputer for large-scale AI model training, enabling adaptive, data-driven decisions during experiments. This framework optimizes neutron beam time, improves experimental accuracy, and lays the foundation for automation in neutron scattering. Although real-time experiment steering is still in the proof-of-concept stage, the demonstrated potential of this system offers a substantial reduction in data processing time from hours to minutes via distributed training, and significant improvements in model accuracy, setting the stage for widespread adoption across neutron scattering facilities and more efficient exploration of complex material systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A roadmap toward scaling, reasoning and self-evolving foundation models for nuclear and particle physics

Foundation models have revolutionized artificial intelligence, with Large Language Models demonstrating unprecedented capabilities in multimodal understanding, reasoning and tool use. Nuclear and particle physics stands at a critical juncture where similar transformative potential awaits realization. The field generates exabytes of experimental data, exascale simulations, and decades of theoretical insights — yet these remain largely disconnected from modern Artifical Intelligence (AI) capabilities, with most physics AI applications confined to narrow, task-specific models that suffer from domain shifting when applied to real experimental data. We present a roadmap for FM4NPP (Foundation Model for Nuclear and Particle Physics), systematically scaling from current proof-of-concept models to trillion-parameter architectures capable of autonomous discovery. Our approach advances three critical frontiers: unified data infrastructure integrating detector data, scientific knowledge and computational tools across global facilities; multi-facility foundation models enabling cross-experiment knowledge transfer and accelerated discovery; and agentic AI capabilities for reasoning and autonomous tool use. The resulting self-evolving FM4NPP will transform physics research by converting time-intensive data analysis, theory derivation and computational bottlenecks into rapid AI–human collaborative discovery. This paradigm shift promises to fundamentally accelerate scientific progress in nuclear and particle physics, enabling researchers to focus on high-level insights while AI handles routine analysis and explores vast parameter spaces beyond human capacity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2004

The Space Technology 5 Avionics System

The Space Technology 5 (ST5) mission is a NASA New Millennium Program project that will validate new technologies for future space science missions and demonstrate the feasibility of building launching and operating multiple, miniature spacecraft that can collect research-quality in-situ science measurements. The three satellites in the ST5 constellation will be launched into a sun-synchronous Earth orbit in early 2006. ST5 fits into the 25-kilogram and 24-watt class of very small but fully capable spacecraft. The new technologies and design concepts for a compact power and command and data handling (C&DH) avionics system are presented. The 2-card ST5 avionics design incorporates new technology components while being tightly constrained in mass, power and volume. In order to hold down the mass and volume, and quali& new technologies for fUture use in space, high efficiency triple-junction solar cells and a lithium-ion battery were baselined into the power system design. The flight computer is co-located with the power system electronics in an integral spacecraft structural enclosure called the card cage assembly. The flight computer has a full set of uplink, downlink and solid-state recording capabilities, and it implements a new CMOS Ultra-Low Power Radiation Tolerant logic technology. There were a number of challenges imposed by the ST5 mission. Specifically, designing a micro-sat class spacecraft demanded that minimizing mass, volume and power dissipation would drive the overall design. The result is a very streamlined approach, while striving to maintain a high level of capability, The mission's radiation requirements, along with the low voltage DC power distribution, limited the selection of analog parts that can operate within these constraints. The challenge of qualifying new technology components for the space environment within a short development schedule was another hurdle. The mission requirements also demanded magnetic cleanliness in order to reduce the effect of stray (spacecraft-generated) magnetic fields on the science-grade magnetometer.

Speer, Dave↗
NASA NTRS2014

Wake Vortex Detection: Phased Microphone vs. Linear Infrasonic Array

Sensor technologies can make a significant impact on the detection of aircraft-generated vortices in an air space of interest, typically in the approach or departure corridor. Current state-of-the art sensor technologies do not provide three-dimensional measurements needed for an operational system or even for wake vortex modeling to advance the understanding of vortex behavior. Most wake vortex sensor systems used today have been developed only for research applications and lack the reliability needed for continuous operation. The main challenges for the development of an operational sensor system are reliability, all-weather operation, and spatial coverage. Such a sensor has been sought for a period of last forty years. Acoustic sensors were first proposed and tested by National Oceanic and Atmospheric Administration (NOAA) early in 1970s for tracking wake vortices but these acoustic sensors suffered from high levels of ambient noise. Over a period of the last fifteen years, there has been renewed interest in studying noise generated by aircraft wake vortices, both numerically and experimentally. The German Aerospace Center (DLR) was the first to propose the application of a phased microphone array for the investigation of the noise sources of wake vortices. The concept was first demonstrated at Berlins Airport Schoenefeld in 2000. A second test was conducted in Tarbes, France, in 2002, where phased microphone arrays were applied to study the wake vortex noise of an Airbus 340. Similarly, microphone phased arrays and other opto-acoustic microphones were evaluated in a field test at the Denver International Airport in 2003. For the Tarbes and Denver tests, the wake trajectories of phased microphone arrays and lidar were compared as these were installed side by side. Due to a built-in pressure equalization vent these microphones were not suitable for capturing acoustic noise below 20 Hz. Our group at NASA Langley Research Center developed and installed an infrasonic array at the Newport News-Williamsburg International Airport early in the year 2013. A pattern of pressure burst, high-coherence intervals, and diminishing-coherence intervals was observed for all takeoff and landing events without exception. The results of a phased microphone vs. linear infrasonic array comparison will be presented.

Shams, Qamar A.↗
DOE OSTI2025

Generalized fiducial inference on differentiable manifolds

We introduce a novel approach to inference on parameters that take values in a Riemannian manifold embedded in a Euclidean space. Parameter spaces of this form are ubiquitous across many fields, including chemistry, physics, computer graphics, and geology. Here, this new approach uses generalized fiducial inference (GFI) to obtain a posterior-like distribution on the manifold, without needing to know local parameterizations that map to the constrained space from an unconstrained Euclidean space. Using mathematical tools from Riemannian geometry, we construct a constrained generalized fiducial distribution (CGFD). A Bernstein-von Mises-type result for the CGFD, which provides intuition for how the desirable asymptotic qualities of the unconstrained generalized fiducial distribution are inherited by the CGFD, is provided. To illustrate the practical use of the CGFD, we provide a proof-of-concept example in the context of a linear logspline density estimation problem, and demonstrate that CGFD-based confidence sets exhibit desirable coverage properties via simulation. As an application, we fit a CGFD to COVID-19 case count data from North Carolina, USA.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

The Hydropower Game: An Interactive Learning Tool for the Future Hydropower Workforce

This report documents a Seedling project supported by the U.S. Department of Energy (DOE) Water Power Technologies Office (WPTO), conducted by Argonne National Laboratory (ANL) and the National Laboratory of the Rockies (NLR). The Seedling and Sapling Program provides small grants over short duration to enable early-stage research at national laboratories. This funding mechanism is intended to cultivate innovative ideas and expand research road maps in hydropower and marine energy technologies. Under this Seedling award, the project team developed an educational outreach tool, or “serious game”, built in Python and powered by the Pygame library, aimed at teaching fundamental hydropower concepts through an engaging, interactive learning experience. The game features multiple lessons covering several hydropower topics while allowing for expansion and customization in the instance of future funding availability: • Hydropower Plant Types: Players explore and compare the mechanics and applications of run-of-river, dam hydropower, and pumped-storage hydropower. • Flow Dynamics and Power Generation: Interactive tasks demonstrate how release rate and hydraulic head combine to determine power output. • Grid Operations and Load Following: Simulations illustrate how hydropower facilities respond to fluctuating electricity demand to balance the grid. • Market Integration: Levels scaffold understanding of how hydropower interfaces with the broader energy market, including operational and economic considerations. The tool was showcased at several science, technology, engineering, and mathematics (STEM) outreach events, where it was demoed to students, educators, and the general public. These events provided valuable opportunities to collect feedback on the gameplay, storyline, and educational objectives from a wide audience. The game was presented at STEMapalooza, Introduce a Girl to Engineering Day, STEMCON, and Clean Currents 2025. Insights gathered during these demonstrations informed refinements to the game’s user experience and strengthened its effectiveness as an educational tool for teaching hydropower concepts. This report outlines the game’s design philosophy, educational objectives, technical implementation, user experience insights, and potential for broader deployment within educational and workforce development contexts. It emphasizes how gamified learning can demystify complex hydropower science and inspire interest in water-power technologies. The project’s success demonstrates the value of Seedling funding in fostering creative, lowcost educational tools that support DOE’s mission to advance energy literacy and innovation. The report concludes with recommendations for expanding the tool by adding new levels, integrating assessment metrics, and exploring commercialization or deployment pathways through future Sapling funding. The official webpage of the Hydropower Game, which includes a link to the educational tool, can be accessed at www.anl.gov/hydropower/hydropower-game.

13 HYDRO ENERGY↗
DOE OSTI2020

High Temperature Additive Architectures for 65% Efficiency (Final Report)

GE Power (GEP) proposed a development program that targets advanced high temperature additive components that contribute towards the DOE’s goal for advanced gas turbines that are capable of 65%, or greater, efficiency in combined cycle application. GEP proposed to leverage state-of-the-art additive manufacturing to develop novel and innovative component airfoil and end wall architectures that provide cooling flow savings while maintaining the component durability expected in today’s gas turbines. The objective of this program was to develop advanced component designs and architectures enabled by additive manufacturing, and the materials systems and additive manufacturing technology required for these designs. This Phase I program leveraged existing design and analysis knowledge and techniques for additive materials and methods and utilized extensive analytical evaluations to develop and refine designs for advanced turbine hot gas path (HGP) components. The design will be the basis for development and testing in a potential Phase II program. The goal of this Phase I program was to establish a feasible conceptual design for advanced additive turbine hot section components along with a technology maturation plan involving testing to address risk areas and needed validation. It was approached through two primary elements: 1) conceptual design and analysis of wall architectures, advanced airfoil cooling concepts, and advanced system-level concepts, and 2) investigation of additive modalities and associated materials systems. The Phase I program has concluded with the down-select of a primary design concept for a potential Phase II program.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Optimization of Archimedes Screw for Use in Hydroelectric Projects

In 2017, the Department of Energy’s (DOE) Water Power Technologies Office (WPTO) made federal funding available to several awardees to investigate and provide innovative technological solutions to reduce capital costs of installed hydroelectric facilities at non-powered dam’s (NPD’s) across the United States, while maintaining a high level of efficiency. Awardees were to develop specific technologies that showed promise of reducing installed capital cost (ICC) by at least 20% over a given baseline and maintain a water-to-wire efficiency of at least 80% at head levels of 50 feet or less and flows of 1000 cubic feet per second (cfs) or less. Canyon Hydro (Canyon) was selected as an awardee for this funding and worked to refine the implementation of the Archimedes screw turbine for use at these site conditions. Canyon and its project partners analyzed several dam inventory datasets to determine the most common head and flow range of current NPD’s in order to best select design conditions for a turbine that would perform successfully at common heads and flows. Computational Fluid Dynamic (CFD) analyses were conducted after site conditions had been selected to optimize the turbine geometry for efficiency. Through this effort we were able to estimate water-to-wire efficiency over a range of flows. Equipment design focused on concepts of modularity and pre-fabricated construction. These methodologies were used where possible to reduce costly on-site construction and shorten deployment timelines. Cost modeling was conducted with input from industry experts in general construction, pre-fabricated concrete construction, and composite fabrication. As a hydroelectric turbine manufacturer of 35 years, Canyon drew upon its own knowledge base in steel fabrication, water-to-wire component specification and ancillary systems to develop the remaining cost matrix for the project. As a result of these efforts, Canyon was able to present findings that indicated a modular Archimedes screw turbine system could be designed that reduced ICC by 23.9% and maintain a maximum water-to-wire efficiency of 82.3%, meeting the goals of the project.

13 HYDRO ENERGY↗
NASA NTRS2001

Geoscience Laser Altimeter System (GLAS) Instrument: Flight Loop Heat Pipe (LHP) Acceptance Thermal Vacuum Test

Two loop heat pipes (LHPs) are to be used for tight thermal control of the Geoscience Laser Altimeter System (GLAS) instrument, planned for flight in late 2001. The LHPs are charged with Propylene as a working fluid. One LHP will be used to transport 110 W from a laser to a radiator, the other will transport 160 W from electronic boxes to a separate radiator. The application includes a large amount of thermal mass in each LHP system and low initial startup powers. The initial design had some non-ideal flight design compromises, resulted in a less than ideal charge level for this design concept with a symmetrical secondary wick. This less than ideal charge was identified as the source of inadequate performance of the flight LHPs during the flight thermal vacuum test in October of 2000. We modified the compensation chamber design, re-built and charged the LHPs for a final LHP acceptance thermal vacuum test. This test performed March of 2001 was 100% successful. This is the last testing to be performed on the LHPs prior to instrument thermal vacuum test. This sensitivity to charge level was shown through varying the charge on a Development Model Loop Heat Pipe (DM LHP) and evaluating performance at various fill levels. At lower fills similar to the original charge in the flight units, the same poor performance was observed. When the flight units were re-designed and filled to the levels similar to the initial successful DM LHP test, the flight units also successfully fulfilled all requirements. This final flight Acceptance test assessed performance with respect to startup, low power operation, conductance, and control heater power, and steady state control. The results of the testing showed that both LHPs operated within specification. Startup on one of the LHPs was better than the other LHP because of the starter heater placement and a difference in evaporator design. These differences resulted in a variation in the achieved superheat prior to startup. The LHP with the lower superheat was sensitive to the thermal environment around the compensation chamber, while the LHP with the higher superheat (similar in design to DM LHP) was not. In response to the test results the placement of the starter heater will be optimized for the flight instrument testing for higher achieved superheat. This presentation discusses startup behavior, overall conductance of a radiator system, low power operation, high power operation, temperature control stability, and control heater power requirements as measured during this acceptance thermal vacuum test. A brief summary of 'lessons learned' will be included.

Baker, Charles↗
DOE OSTI2020

Precise Experimental Test of the Luttinger Theorem and Particle-Hole Symmetry for a Strongly Correlated Fermionic System

A fundamental concept in physics is the Fermi surface, the constant-energy surface in momentum space encompassing all the occupied quantum states at absolute zero temperature. In 1960, Luttinger postulated that the area enclosed by the Fermi surface should remain unaffected even when electron-electron interaction is turned on, so long as the interaction does not cause a phase transition. Understanding what determines the Fermi surface size is a crucial and yet unsolved problem in strongly interacting systems such as high-$T_c$ superconductors. Here we present a precise test of the Luttinger theorem for a two-dimensional Fermi liquid system where the exotic quasiparticles themselves emerge from the strong interaction, namely, for the Fermi sea of composite fermions (CFs). Via direct, geometric resonance measurements of the CFs’ Fermi wave vector down to very low electron densities, we show that the Luttinger theorem is obeyed over a significant range of interaction strengths, in the sense that the Fermi sea area is determined by the density of the minority carriers in the lowest Landau level. Our data in this work also address the ongoing debates on whether or not CFs obey particle-hole symmetry, and if they are Dirac particles. We find that particle-hole symmetry is obeyed, but the measured Fermi sea area differs quantitatively from that predicted by the Dirac model for CFs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Delivery of Dynamic Thermal Energy Storage Models and Advanced Reactor Concept Models to the HYBRID Repository

This publication details newly created energy storage and reactor models developed within the HYBRID modeling repository as part of the Department of Energy Office of Nuclear Energy (DOE-NE) Integrated Energy Systems (IES) program, led by Idaho National Laboratory (INL). Model development to-date includes creation of dynamic systems-level models of a pebble bed high temperature gas reactor (HTGR), sodium fast reactor (SFR), compressed air energy storage (CAES), liquid air energy storage (LAES) and Modelica standard library based two-tank sensible heat storage (SHS) in the IES-based HYBRID repository. Models are developed using the latest publicly available data and incorporate the possibility of control strategy inclusion for use with the existing IES modeling, analysis, and optimization toolset. Simulations showcase the abilities of each technology to flexibly operate in ways consistent with IES operation expectations. When these models are available, they can be utilized within different integrated energy park concepts to understand optimal system operation, control, and dispatching. Moreover, given the generic nature of the models, industrial partner technologies can be quickly added to the repository using the existing models as a basis. Additional dynamic models for thermal energy storage concepts can be developed and added to the HYBRID repository as needed. Also detailed in this report are future development goals for the HYBRID repository including adding suites of steady-state models, economic costing information, and reduced-order models. By adding these models in addition to the physical transient models currently existing within HYBRID, HYBRID will be a fully integrable tool for FORCE users.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Latent diffusion can map beam loss to two-dimensional phase-space projections

Beam loss monitors (BLMs) and beam current monitors (BCMs) are ubiquitous at particle accelerators around the world. These simple devices provide noninvasive high-level beam measurements but give no insight into the detailed 6D (𝑥,𝑦,𝑧,𝑝 𝑥 ,𝑝 𝑦 ,𝑝 𝑧 ) beam phase-space distributions or dynamics. We show that generative conditional latent diffusion models can learn intricate patterns to solve the extreme inverse problem of mapping waveforms of tens of BLMs or BCMs along an accelerator to detailed 2D projections of a charged particle beam’s 6D phase-space density. This transformational method can be used at any particle accelerator to transform simple noninvasive devices into detailed beam phase-space diagnostics. We demonstrate this concept via multiparticle simulations of the high-intensity beam in the kilometer-long Los Alamos Neutron Science Center linear proton accelerator.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Results and lessons learned from accelerating radio frequency modeling using machine learning [slides]

The “advanced tokamak” reactor concept is a leading candidate for a steady state fusion pilot plant. An advanced tokamak (AT) sustains a majority of the required plasma current with effects resulting from maintenance of the peaked pressure at the device center. This current is augmented by auxiliary current drive sources. These auxiliary actuators may consist of neutral particle beams and/or radio frequency (RF) systems such as lower hybrid current drive (LHCD) and high harmonic fast wave (HHFW) current drive using radio and microwaves from antennas. The primary focus of this work is to develop models of RF current profile control suitable for use in integrated modeling frameworks and for real-time control in experiments. Direct physics models of RF current drive can be computationally intensive. In order to achieve predictive times appropriate for the thousands of calls needed in real-time control of experiments and for use in integrated models, we will apply modern machine learning (ML) techniques to accelerate these models and interpolate their results. To generate the fast and accurate models for use in control level algorithms and integrated modeling we need to replace present models with high dimensional interpolation of their results. We will perform additional simulations across a broader parameter range for EAST and other tokamaks in different physics regimes (Alcator C-Mod, DIII-D, WEST, CFETR, ARC, ITER) and combine them into a larger database for training and testing of the ML models. Further testing of the control level models with experimental current profile data from EAST and C-Mod tokamaks will provide additional confirmation of the control level model before integration in a tokamak control system or integrated modeling suite. ML will be used to optimize the selection of training data consisting of RF current driven at different values of density profile, temperature profile, plasma current, and wavenumber. ML will also be used to facilitate classification of current drive from these input data. The output of this effort will be a validated classifier capable of determining the current drive profiles for HHFW CD and LHCD on a mille-second timescale. This will provide a breakthrough capability enabling real-time control of RF driven current profiles in experiments including ITER ICRF and use integrated modeling frameworks requiring thousands of current profile calculations in discharge simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2023

Real-Time Hardware-in-the-Loop Evaluation of A Partially Turboelectric Propulsion Control Design

In support of aviation fuel burn and emission reduction goals, NASA is pursuing high-payoff research investments that promise to transform aviation. This includes investments in Electrified Aircraft Propulsion (EAP). Multiple technology challenges must be addressed to unlock the full potential of EAP. This includes addressing challenges related to propulsion controls, which will be vital for ensuring efficient coordinated operation of EAP subsystems. This paper presents results from real-time hardware-in-theloop (HIL) testing of a control design for a single aisle partially-turboelectric aircraft propulsion concept conducted at the NASA Electric Aircraft Testbed (NEAT) facility. The control system under test is designed for a propulsion concept consisting of two wing-mounted turbofan engines that produce thrust and generate electrical power to drive a boundary layer ingesting tailfan propulsor via an electrical motor. An integrated control strategy is applied to ensure coordinated operation of the turbofan and tailfan subsystems during steady-state and transient operation throughout the flight envelope. The NEAT test of this integrated control design consists of a partially HIL, partially simulated configuration. A subscale representation of the electrical system design is implemented in hardware and mechanically coupled to electric machines that emulate turbomachinery and propulsor shaft dynamics. The hardware configuration is then operated under the control of a real-time computer application that runs a simulation of the propulsion system and the developed control logic. The NEAT facility test campaign includes a series of experiments that subject the control design to throttle transients conducted throughout the flight envelope and full-flight mission profiles. Testing under simulated performance degradation is also conducted to evaluate control design robustness. This includes constant and abrupt changes in degradation levels. Results from the HIL test are presented and shown to be in good agreement with pretest simulation predictions demonstrating the efficacy of the integrated control design approach.

Electrified Aircraft Propulsion↗
NASA NTRSDate not supplied

Using Global Market Demand Analysis to Guide Conceptual Design of Low-Boom Supersonic Transports

This paper uses a mathematical framework to identify the interdependencies of key variables in supersonic transportation demand analysis. The existing quantitative models for supersonic transportation demand analysis are compared for consistency in modeling the interdependencies. Unlike other quantitative models, the Low-Boom Systems Analysis Model (LBSAM2) can propagate important design characteristics of a supersonic transport aircraft concept to the level of economic metrics (such as the number of future supersonic passengers), with a consistent coupling of the market demand analysis, detailed mission analysis, and low-boom constraint. This allows the use of the detailed demand analysis results from LBSAM2 to maximize the economic viability of a supersonic transport aircraft by finding favorable system-level trades between weight, range, fuel burn, and assumed sonic boom ground noise limit for supersonic overland flight. In this paper, LBSAM2 is integrated with conceptual low-boom design to improve the economic viability of low-boom supersonic transport aircraft. A brief discussion of uncertainties in the LBSAM2 analysis is also included, focusing on their impacts on the relative economic advantages between low-boom concepts.

Consistent coupling of disciplinary analyses↗
NASA NTRS2024

Snow4Flow: Concept Paper for a NASA Earth Venture Suborbital-4 Investigation

Snow4Flow was proposed as a large ($30M cost cap) Earth Venture Suborbital (EVS-4) mission in April 2023 and selected as such in April 2024. It will commence pending an Investigation Confirmation Review in 2025. Its airborne and ground campaigns are presently expected to occur in March–May 2027–2029. Quantifying the ongoing retreat of glaciers and ice sheets – and projecting their futures – are major societal concerns due to their contribution to sea-level rise and influence on water resources, natural hazards, and associated socioeconomic impacts. The ability to confidently project glacier and ice-sheet mass change is limited by a severe lack of observations that reliably constrain both their input (Snow) and output (Flow) mass fluxes. Snow4Flow will capture the spatial variability in snow accumulation and ice volume across 4 Northern Hemisphere (NH) regions containing hundreds of rapidly changing glaciers to deliver more reliable, societally relevant projections of land-ice change. This major advance requires spatially extensive radar-sounding surveys that are not possible from orbit (Fig. 1). This EVS-4 mission will drive foundational improvements to NH land-ice boundary conditions and forcing data – including orographic precipitation patterns in alpine environments, ice thickness and subglacial topography – and directly leverages them into state-of-the-art models and projections. Our key science questions are: 1. How will NH glaciers respond to climate change through the end of the 21st century? 2. How does snow accumulation vary in regions of high topographic relief?

Jack W Holt↗
DOE OSTI2021

Cybersecurity for Grid Connected eXtreme Fast Charging (XFC) Station (CyberX) (Final Scientific/Technical Report)

This report summarizes the activities conducted under the DOE VTO funded project DE- EE0008451, where ABB Inc. (ABB), in collaboration with Idaho National Laboratory (INL), APS Global (APS), and XOS Trucks (XOS) pursued the development of a cyber-resilient extreme fast charging (XFC) management system. This project entitled Cybersecurity for Grid Connected eXtreme Fast Charging (XFC) Station (CyberX) focuses on a resilient architecture for smart charging EV Supply Equipment (EVSE) device control and Coordinated Anomaly Detection System (CADS) features that can be added at the charging site depot level to increase cybersecurity. The project was split into two budget periods focused first on developing the threat model and resilient control concepts and second on testing, improving, and validating those developed resilient control algorithms and features with a focus on key vulnerabilities identified during the threat assessment portion of the project. During the first budget period of the CyberX project, the ABB led team focused on activities to identify, model, and quantitatively prioritize high-impact attack scenarios with potential cyber-physical effects while also modeling and developing concepts for a resilient control system that could securely address integration of DERs and other resources with EV charging. Development of the security focused XFC management system (XMS) was accomplished first by offline simulation using a developed XFC station or depot with 480V input level and simulating measurement inputs to monitoring and control systems in concept development. A representative distribution grid model was developed supporting an EV charging site model with BESS and 6 general EV charging models. These EV charging models allowed multiple configurations of charging level, multiple connected protection and measurement devices, and simulation function to show general compromise of EV, BESS, and protection features based on parallel threat analysis. During the second budget period, the EV site and supporting systems model was developed in more detail and converted from offline model to real-time to real-time with EV charging hardware in the loop (HIL). The resilient control architecture developed as concept in the first part of the project was further tested and validated for integration of local energy resources and XFC charging station site equipment while maintaining cybersecure operating principles. The proposed resilient architecture for smart charging and cybersecurity features consists of two main concepts developed and tested within the project. The first concept is an XFC management system (XMS) consisting of a hardware gateway, software platform, and Supervisory Control and Data Acquisition (SCADA) or Distribution Management System integration components. The second concept is a Coordinated Anomaly Detection System (CADS) which forms a primarily software-related subsystem of the total CyberX solution focused on monitoring system measurements, estimation of measurement states, and predicting current at the utility point of interaction based on machine learning for anomaly detection.

33 ADVANCED PROPULSION SYSTEMS↗