Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Optimized Route Capability”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Treyson Ricks - Intern Showcase Poster

Quinone-based sorbents offer a tunable, energy-efficient route to electrochemical CO2 capture, but systematic guidance for molecular design is lacking. Here, we report a high-throughput computational workflow that combines density functional theory (DFT) screening with machine-learning (ML) modeling to evaluate CO2 binding thermodynamics across several quinone derivatives, spanning benzoquinones, naphthoquinones, and anthraquinones. In addition to using solvents to stabilize the quinone anion and dianion, we studied the effect of ion-pairing on the reduction potentials and the CO2 binding energy. Automated Python scripts handled geometry optimizations and adduct-formation energies on an HPC cluster, reducing manual effort significantly. This integrated platform can uncover structure–property relationships and enables rapid in silico evaluation of untested candidates. We present one example from our workflow to showcase the capability of using quinones with ion-pairing to effectively capture CO2. Our approach paves the way for the rational selection of optimal quinone sorbents and can be extended with experimental thermochemical and kinetic data, alternative redox cycles, and stability assessments to accelerate development of next-generation electrochemical CO2 capture materials.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗
NASA NTRS1996

Advanced Intelligent System Application to Load Forecasting and Control for Hybrid Electric Bus

The primary motivation for this research emanates from providing a decision support system to the electric bus operators in the municipal and urban localities which will guide the operators to maintain an optimal compromise among the noise level, pollution level, fuel usage etc. This study is backed up by our previous studies on study of battery characteristics, permanent magnet DC motor studies and electric traction motor size studies completed in the first year. The operator of the Hybrid Electric Car must determine optimal power management schedule to meet a given load demand for different weather and road conditions. The decision support system for the bus operator comprises three sub-tasks viz. forecast of the electrical load for the route to be traversed divided into specified time periods (few minutes); deriving an optimal 'plan' or 'preschedule' based on the load forecast for the entire time-horizon (i.e., for all time periods) ahead of time; and finally employing corrective control action to monitor and modify the optimal plan in real-time. A fully connected artificial neural network (ANN) model is developed for forecasting the kW requirement for hybrid electric bus based on inputs like climatic conditions, passenger load, road inclination, etc. The ANN model is trained using back-propagation algorithm employing improved optimization techniques like projected Lagrangian technique. The pre-scheduler is based on a Goal-Programming (GP) optimization model with noise, pollution and fuel usage as the three objectives. GP has the capability of analyzing the trade-off among the conflicting objectives and arriving at the optimal activity levels, e.g., throttle settings. The corrective control action or the third sub-task is formulated as an optimal control model with inputs from the real-time data base as well as the GP model to minimize the error (or deviation) from the optimal plan. These three activities linked with the ANN forecaster proving the output to the GP model which in turn produces the pre-schedule of the optimal control model. Some preliminary results based on a hypothetical test case will be presented for the load forecasting module. The computer codes for the three modules will be made available fe adoption by bus operating agencies. Sample results will be provided using these models. The software will be a useful tool for supporting the control systems for the Electric Bus project of NASA.

Momoh, James↗
DOE OSTI2026

Biomanufacturing and Scale-Up: Pathways to Biochemicals, Biofuels, and Biomaterials

Advancing the bioeconomy requires the development of large-scale microbial bioprocesses capable of converting waste carbon streams into biofuels, biochemicals, and biomaterials at industrially relevant scales. While biomanufacturing has been successfully demonstrated at the laboratory scale for a wide range of chemicals, only a few have reached industrial-scale production. This is partly due to the inherent complexity of microbial systems, which rely on living cells with intricate metabolic pathways that are highly sensitive to environmental changes, making large-scale production difficult to optimize and predict. As a result, scaling-up bioprocesses remains a high-stakes challenge that requires deeper exploration. This involves integrating feedstock and microbial selection, upstream and downstream processes, and computational modelling, among other research efforts. Bulk and specialty chemicals derived from biological processes also face competition from fossil-based production routes, which have been refined through decades of technological advancements. While biologically derived molecules may offer more environmentally friendly production pathways than traditional chemical manufacturing, their widespread adoption depends on achieving cost parity-or superiority-relative to fossil-based methods. This emphasizes the importance of holistic research, including techno-economic analyses and life cycle assessments, to ensure both economic viability and environmental sustainability. This editorial and special issue explores state-of-the-art strategies for converting waste carbon sources into valuable products. It discusses how enzymes, single microbes (e.g., extremophiles), and microbiomes (e.g., through division of labor) can be integrated with upstream and downstream process innovations-such as consolidated bioprocessing and in situ product recovery-to improve the efficiency and scalability of biomanufacturing. The editorial further highlights the role of computational modelling in understanding, predicting, and controlling bioprocess performance across scales, and concludes by emphasizing the importance of techno-economic modelling to identify technologies that can move to market.

09 BIOMASS FUELS↗
DOE OSTI2023

Enhanced Electrochemical Performance of Disordered Rocksalt Cathodes Enabled by a Graphite Conductive Additive

Cobalt-free cation-disordered rocksalt (DRX) cathodes are a promising class of materials for next-generation Li-ion batteries. Although they have high theoretical specific capacities (>300 mA h/g) and moderate operating voltages (~3.5 V vs Li/Li + ), DRX cathodes typically require a high carbon content (up to 30 wt %) to fully utilize the active material which has a detrimental impact on cell-level energy density. To assess pathways to reduce the electrode’s carbon content, the present study investigates how the carbon’s microstructure and loading (10–20 wt %) influence the performance of DRX cathodes with the nominal composition Li 1.2 Mn 0.5 Ti 0.3 O 1.9 F 0.1 . While electrodes prepared with conventional disordered carbon additives (C65 and ketjenblack) exhibit rapid capacity fade due to an unstable cathode/electrolyte interface, DRX cathodes containing 10 wt % graphite show superior cycling performance (e.g., reversible capacities ~260 mA h/g with 85% capacity retention after 50 cycles) and rate capability (~135 mA h/g at 1000 mA/g). Furthermore, a suite of characterization tools was employed to evaluate the performance differences among these composite electrodes. Overall, these results indicate that the superior performance of the graphite-based cathodes is largely attributed to the: (i) formation of a uniform graphitic coating on DRX particles which protects the surface from parasitic reactions at high states of charge and (ii) homogeneous dispersion of the active material and carbon throughout the composite cathode which provides a robust electronically conductive network that can withstand repeated charge–discharge cycles. Overall, this study provides key scientific insights on how the carbon microstructure and electrode processing influence the performance of DRX cathodes. Based on these results, exploration of alternative routes to apply graphitic coatings is recommended to further optimize the material performance.

25 ENERGY STORAGE↗
NASA NTRS2012

Preliminary Benefits Assessment of Traffic Aware Strategic Aircrew Requests (TASAR)

While en route, aircrews submit trajectory change requests to air traffic control (ATC) to better meet their objectives including reduced delays, reduced fuel burn, and passenger comfort. Aircrew requests are currently made with limited to no information on surrounding traffic. Consequently, these requests are uninformed about a key ATC objective, ensuring traffic separation, and therefore less likely to be accepted than requests informed by surrounding traffic and that avoids creating conflicts. This paper studies the benefits of providing aircrews with on-board decision support to generate optimized trajectory requests that are probed and cleared of known separation violations prior to issuing the request to ATC. These informed requests are referred to as traffic aware strategic aircrew requests (TASAR) and leverage traffic surveillance information available through Automatic Dependent Surveillance Broadcast (ADS-B) In capability. Preliminary fast-time simulation results show increased benefits with longer stage lengths since beneficial trajectory changes can be applied over a longer distance. Also, larger benefits were experienced between large hub airports as compared to other airport sizes. On average, an aircraft equipped with TASAR reduced its travel time by about one to four minutes per operation and fuel burn by about 50 to 550 lbs per operation depending on the objective of the aircrew (time, fuel, or weighted combination of time and fuel), class of airspace user, and aircraft type. These preliminary results are based on analysis of approximately one week of traffic in July 2012 and additional analysis is planned on a larger data set to confirm these initial findings.

Henderson, Jeff↗
NASA NTRS2019

Effect of Out-Gassing on the Onset of Hypersonic Boundary Layer Transition

Prediction and control of the onset of transition and the associated variation in aerothermodynamic parameters in high-speed flows is key to optimize the performance and design of Thermal Protection Systems (TPS) of next-generation aerospace vehicles [1]. Boundary Layer Transition (BLT) characteristics can influence the surface heating budget determining the TPS thickness and consequently its weight penalty. Ablative heatshields are designed to alleviate the high heat flux at the surface through pyrolysis of their polymeric matrix and subsequent fiber ablation [2]. Pyrolysis leads to out-gassing and non-uniform ablation lead to surface roughness, both of which are known to influence the transition process. An ablator impacts BLT through three main routes: gas injecting into the boundary layer from the wall, changing the surface heat transfer due to wall-flow chemical reactions, and modifying surface roughness [3]. In preparation to Mars 2020 mission post-flight analysis, the predictive transition capability has been initiated toward hard-coupling porous material response analysis and aerothermal environment calculation.

Karimi, Mona↗
NASA NTRSDate not supplied

Advancing Autonomy in Distributed Space Systems: Insights From on-Orbit Testing with the Starling 1.0 Mission

Autonomous decision-making is crucial for enhancing mission effectiveness in Distributed Space Systems (DSS), particularly in multi-spacecraft operations where communication constraints and mission complexity pose challenges. The Distributed Spacecraft Autonomy (DSA) team at NASA’s Ames Research Center is advancing autonomy in DSS through five key technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. The DSA experiment onboard the Starling 1.0 Mission showcases collaborative resource allocation for multi-point science data collection with four small spacecraft. Autonomy in decision-making is highlighted as a crucial factor for multi-spacecraft missions, enabling spacecraft to operate independently, reducing reliance on ground control. This capability is particularly significant for future deep-space missions, where communication delays and limited data transmission capacity make traditional command and control approaches impractical. This demonstration focuses on a GPS Channel Selection Experiment, leveraging emergent capabilities like "shared sampling" and "simultaneous sampling" to optimize channel selection across the spacecraft swarm. The experiment aims to capture ionospheric phenomena such as the Equatorial Ionization Anomaly and Polar Patches. The DSA system's autonomous reconfiguration ability is showcased, emphasizing its adaptability to natural phenomena without significant integration efforts. The GPS Channel Selection Experiment utilizes a dual-band GPS receiver to estimate plasma density in the ionosphere. Explorative and exploitative channel selections are employed based on the nature of observed phenomena. The performance of DSA algorithms is evaluated in terms of optimal channel allocations and responsiveness to changes in observed features. The DSA Flight Software utilizes the Core Flight System (cFS) framework, ensuring compatibility with the Starling 1.0 flight mission software. DSA showcases results from RTI’s Connext DDS Micro communication middleware, enabling message routing over the Ad-Hoc Network of Starling 1.0. This paper provides a comprehensive overview of the DSA experiment's initial results, emphasizing the advancements in autonomy for Distributed Space Systems and the successful collaboration with the Starling 1.0 mission.

Caleb Ashmore Adams↗
DOE OSTI2026

Gradient-informed Hamiltonian Monte Carlo for multicomponent CALPHAD model optimization and uncertainty quantification

CALPHAD model parameter optimization is inherently challenging due to non-smooth objective functions, high-dimensional parameter spaces, and the need for uncertainty quantification (UQ). Traditional weighted nonlinear least squares approaches are computationally efficient but local, whereas black-box global optimizers and ensemble Markov Chain Monte Carlo (MCMC) methods provide broader exploration at substantial computational cost. The objective of this work is to combine the global exploration capability of gradient-informed Hamiltonian Monte Carlo – specifically the No-U-Turn Sampler (NUTS) – with local deterministic refinement using BFGS to efficiently optimize multicomponent CALPHAD models with minimal manual intervention. Analytic gradients are computed via the Jansson derivative framework. The methodology is demonstrated on the Cr—Fe binary system and extended to the Cr—Fe—Ni ternary system with 32 degrees of freedom. For Cr—Fe, NUTS achieves comparable or superior optimality relative to ensemble MCMC while requiring over an order-of-magnitude fewer likelihood evaluations. Parameter uncertainties are quantified through NUTS sampling and propagated to thermodynamic observables using local expansion, demonstrating a novel modular approach that combines binary and ternary parameter subsets without requiring global relaxation. These results establish gradient-informed exploration as a scalable strategy for multicomponent CALPHAD optimization and provide a practical route towards efficient higher-order database development with quantified uncertainty.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Additive Manufacturing of Hierarchical Multi-Phase High-Entropy Alloys for Nuclear Component

In recent years, high entropy alloys (HEAs), composed of four or more metallic elements mixed in equal or near equal atomic percent, have attracted significant attention due to their excellent mechanical properties and good corrosion resistance. They show significant promise as candidates for high temperature fission and fusion structural applications. However, the conventional synthesis methods are unlikely to present an industrially suitable route for the production and use of HEAs. Recognizing rapidly evolving additive manufacturing (AM) techniques, the goal of this proposal is to optimize the AM process to fabricate HEAs with predesigned chemical compositions and phase morphologies for nuclear components. For this project, two HEAs FeCrNiMn and FeCrNiMnAl have been successfully synthesized. Correlated mechanical response has been systematically characterized under a variety of laser processing and ion irradiations. Both high entropy alloys are found to present comparable swelling and extraordinary irradiation tolerance (limited voids and stabilized phase structure under high irradiation dose). In addition, the microstructure and radiation-induced hardening can be tailored by laser processing under additive manufacturing. And we have assembled at LANL a unique database of HEAs containing a total of 674 compositions with Phase Stability information. Based on this, the machine learning and Artificial Intelligence capability now are established to predict the microstructure of casted HEAs by given chemical compositions. This unique integration will lead to an optimal AM recipe for fabricating radiation tolerant HEAs. The development of both modeling models and experimental capability will also benefit other programs at LANL.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Additive Manufacturing of Cryogenic Austenitic Steel JK2LB via Wire-Fed Directed Energy Deposition (DED) for Fusion Energy Applications

This study explores the feasibility of fabricating cryogenic austenitic steel JK2LB via both laser-based directed energy deposition (laser-DED) and arc-based directed energy deposition (arc-DED) additive manufacturing processes for potential application in fusion reactors. JK2LB, a low-nickel, high-manganese stainless steel developed for ITER, offers excellent cryogenic toughness, radiation resistance, and decay-to-clearance characteristics. Although JK2LB was originally designed to endure cyclic stresses at cryogenic temperatures in tokamaks, its low-temperature mechanical integrity and radiation tolerance also make it a promising candidate for structural components, such as the coil case/support structure in nonplanar high-temperature superconducting magnet assemblies in stellarators. Directed energy deposition (DED) additive manufacturing was selected for this study due to its capability to fabricate large structures with complex geometries. Here, to address the long lead time and high cost associated with acquiring conventional JK2LB solid wire, JK2LB powder-cored wire was developed as the feedstock material. Testing blocks were then fabricated using both wire-fed laser-DED and arc-DED processes. Microstructural and compositional analyses revealed that both DED approaches yield fully austenitic phase and columnar grain structures. Mechanical testing at room temperature revealed that both DED routes achieved yield strength and elongation comparable to those of conventionally processed JK2LB via vacuum melting, electroslag remelting, extrusion, and drawing, though ultimate tensile strength was reduced due to Mn loss and large columnar grains. As a study mainly focusing on the additive manufacturing process, this work demonstrates the potential of additive manufacturing for fusion energy applications and provides a basis for optimization and future cryogenic mechanical evaluation.

Cryogenic steel↗
DOE OSTI2026

Xanthos-Lake Model Source Code

This repository contains the source code for Xanthos-Lake, a lake-modeling extension of the Xanthos framework that introduces a coupled lake component comprising the Xanthos-Lake Snow and Ice Model (xLSIM) and the Xanthos-Lake Water Balance Model (xLWBM). xLSIM is a basin-aware machine-learning model for lake snow, ice, and thermal conditions. It predicts monthly lake ice thickness, snow depth, snow-cover fraction, mixing-layer temperature, and lake ice fraction from meteorological forcing and lake surface-area information. It uses sequence-based deep-learning architectures, including Transformer and hybrid Long Short-Term Memory–Transformer (LSTM–Transformer) models, together with seasonal encoding, multi-lake learning, physical masking, and basin-level cryospheric and non-cryospheric classification. The training workflow uses Ray for scalable execution and includes optional Ray Tune hyperparameter optimization. Model predictions, observations, diagnostics, and feature-importance outputs are written in NetCDF. xLWBM is the water-balance component of the new lake framework. It simulates monthly lake storage, surface area, evaporation, inflow, outflow, and lake–groundwater exchange. It combines physical water-balance equations with calibrated bathymetric relationships, weir-based outlet flow, modified Penman open-water evaporation, groundwater head relaxation, Penman–Monteith snow and ice sublimation, and snow, ice, and thermal conditions supplied by xLSIM. The model calibrates lake parameters against satellite-derived surface-area data, using evaporation-based calibration where surface-area data are unavailable, and supports small, medium, and large lake classes. For large lakes, xLWBM is integrated with the managed-routing workflow so that lake storage and outflow interact directly with downstream river routing and reservoir operations. Together, xLSIM and xLWBM provide Xanthos with a coupled lake-modeling capability. xLSIM supplies the snow, ice, and thermal conditions that affect lake evaporation and snow- and ice-related water exchanges, while xLWBM translates those conditions into dynamic lake storage, surface area, evaporation, and discharge. In return, xLWBM supplies evolving lake surface area to xLSIM. This coupling enables Xanthos to represent lakes as active hydrologic components within basin-scale water-availability and routing simulations.

Machine Learning↗
DOE OSTI2018

The Strategic Benefit of Self Shielded Boxes for Storage and Disposal of Metallic Uranic Material-18141

Sellafield Ltd, on behalf of the Nuclear Decommissioning Authority (NDA), is responsible for the management of a number of facilities whose inventories include a range of metallic uranic material. Additional fuel and fuel bearing materials exist in the NDA estate, some of which are similar to the Sellafield-managed inventory and others present different management challenges. Whilst UK Government policy directs that some of these materials are assets and are therefore managed with eventual future use in mind, there remains a large quantity of material, principally either out-of-scope for reprocessing or which derives from legacy facilities, which is likely to be disposed of to a future Geological Disposal Facility (GDF). The majority of this material is stored under wet conditions to facilitate dose shielding and heat dissipation and will therefore require removal from wet storage, consolidation and conditioning, prior to transfer to GDF. In order to accelerate high hazard and risk reduction by sooner retrieval of legacy material from wetted storage, one of the legacy storage facilities has led technical work to develop the design of Self Shielded Boxes (SSBs) and to substantiate their use for interim storage of the materials in question. Use of the SSBs would represent a change of strategy on the Sellafield Site: historically, timescales for retrieval of material have been reliant upon a waste treatment and storage/disposal route being available. SSBs provide the opportunity to retrieve uranic materials from aging legacy storage facilities for immediate buffer storage, by decoupling the timing of retrieval from the availability of an onward route. An understanding was required of the scope for defining optimal routes for each metallic uranic fuel and fuel bearing material group for safe transport and storage commensurate with current final disposal assumptions and risks, taking into account international best practice. A study is underway to understand options for transfer of material into SSBs, buffer/interim storage locations, treatment/conditioning processes and transport to the GDF. This work forms the basis of a prioritised road-map for the development of routes for study material groups aligned with ongoing and existing planned technical work, which is a pre-requisite to strategy development. The ultimate output of the study will be identification of full life cycle management strategies for metallic uranic material from an enterprise perspective. The combination of this strategic work and ongoing technical work will underpin a series of decisions to divert sub-groups of uranic material away from currently assumed baseline routes in support of earliest practicable hazard and risk reduction. Hence, each decision will reduce the scope of a placeholder future uranic fuel treatment capability, which will diminish the associated British Pound 1 bn capital cost. To date, a technical case for interim storage of uranic material in SSBs has been substantiated for around two thirds of the study materials. The requirement for a new strategy at Sellafield was driven by technical development of SSBs in response to the needs of one programme, but this prompted the study into the potential utilisation of SSBs in order to derive benefit for the wider enterprise and across the NDA estate. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

AVTA Federal Fleet PEV Readiness Data Logging and Characterization Study for the National Park Service: Golden Gate National Recreation Area

Battelle Energy Alliance, LLC, managing and operating contractor for the U.S. Department of Energy's Idaho National Laboratory, is the lead laboratory for U.S. Department of Energy Advanced Vehicle Testing. Battelle Energy Alliance, LLC contracted with Intertek Testing Services, North America (ITSNA) to collect data on federal fleet operations as part of the Advanced Vehicle Testing Activity's Federal Fleet Vehicle Data Logging and Characterization study. The Advanced Vehicle Testing Activity study seeks to collect data to validate the utilization of advanced electric drive vehicle transportation. This report focuses on the Golden Gate National Recreation Area (GGNRA) fleet to identify daily operational characteristics of select vehicles and report findings on vehicle and mission characterizations to support the successful introduction of plug-in electric vehicles (PEVs) into the agencies' fleets. Individual observations of these selected vehicles provide the basis for recommendations related to electric vehicle adoption and whether a battery electric vehicle or plug-in hybrid electric vehicle (PHEV) (collectively PEVs) can fulfill the mission requirements. GGNRA identified 182 vehicles in its fleet, which are under the management of the U.S. General Services Administration. Fleet vehicle mission categories are defined in Section 4, and while the GGNRA vehicles conduct many different missions, only two (i.e., support and law enforcement missions) were selected by agency management to be part of this fleet evaluation. The selected vehicles included sedans, trucks, and sport-utility vehicles. This report will show that battery electric vehicles and/or PHEVs are capable of performing the required missions and providing an alternative vehicle for support vehicles and PHEVs provide the same for law enforcement, because each has a sufficient range for individual trips and time is available each day for charging to accommodate multiple trips per day. These charging events could occur at the vehicle home base, high-use work areas, or intermediately along routes that the vehicles frequently travel. Replacement of vehicles in the current fleet would result in significant reductions in the emission of greenhouse gases and petroleum use, while also reducing fuel costs. The San Francisco Bay Area is a leader in the adoption of PEVs in the United States. PEV charging stations, or more appropriately identified as electric vehicle supply equipment, located on the GGNRA facility would be a benefit for both GGNRA fleets and general public use. Fleet drivers and park visitors operating privately owned PEVs benefit by using the charging infrastructure. ITSNA recommends location analysis of the GGNRA site to identify the optimal placement of the electric vehicle supply equipment station. ITSNA recognizes the support of Idaho National Laboratory and ICF International for their efforts to initiate communication with the National Parks Service and GGNRA for participation in the study. ITSNA is pleased to provide this report and is encouraged by the high interest and support from the National Park Service and GGNRA personnel.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

ProCAFD: Computer-aided Tool for Sustainable Process Synthesis, Intensification and Hybrid solutions

Process industry is always in quest for innovative designs which are both efficient, safe and sustainable. The feasible search space of all unit operations that can be combined to generate process flowsheet alternatives for a given synthesis problem can be large and difficult to manually navigate in order to determine the best processing route. Therefore, it is helpful to utilize computer-aided methods and tools to enumerate, analyze and determine within the design space, the more sustainable processes. In this study, an integrated computer-aided method and corresponding software-tool that’s capable of generating and searching the entire design space for more sustainable process options is presented. In this work a comprehensive analysis method consisting of economic, life cycle, sustainability and process safety indicators is used to identify process bottlenecks on the selected alternative which are translated to design targets. Matching of these design targets minimizes/eliminates the process hot-spots and, thereby generating non-trade-off innovative process designs.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2005

Reactions of Air Transport Flight Crews to Displays of Weather During Simulated Flight

Display of information in the cockpit has long been a challenge for aircraft designers. Given the limited space in which to present information, designers have had to be extremely selective about the types and amount of flight related information to present to pilots. The general goal of cockpit display design and implementation is to ensure that displays present information that is timely, useful, and helpful. This suggests that displays should facilitate the management of perceived workload, and should allow maximal situation awareness. The formatting of current and projected weather displays represents a unique challenge. As technologies have been developed to increase the variety and capabilities of weather information available to flight crews, factors such as conflicting weather representations and increased decision importance have increased the likelihood for errors. However, if formatted optimally, it is possible that next generation weather displays could allow for clearer indications of weather trends such as developing or decaying weather patterns. Important issues to address include the integration of weather information sources, flight crew trust of displayed weather information, and the teamed reactivity of flight crews to displays of weather. Past studies of weather display reactivity and formatting have not adequately addressed these issues; in part because experimental stimuli have not approximated the complexity of modern weather displays, and in part because they have not used realistic experimental tasks or participants. The goal of the research reported here was to investigate the influence of onboard and NEXRAD agreement, range to the simulated potential weather event, and the pilot flying on flight crew deviation decisions, perceived workload, and perceived situation awareness. Fifteen pilot-copilot teams were required to fly a simulated route while reacting to weather events presented in two graphical formats on a separate visual display. Measures of flight crew reactions included performance-based measures such as deviation decision accuracy, and judgment-based measures such as perceived decision confidence, workload, situation awareness, and display trust. Results demonstrated that pilots adopted a conservative reaction strategy, often choosing to deviate from weather rather than ride through it. When onboard and NEXRAD displays did not agree, flight crews reacted in a complex manner, trusting the onboard system more but using the NEXRAD system to augment their situation awareness. Distance to weather reduced situation awareness and heightened workload levels. Overall, flight crews tended to adopt a participative leadership style marked by open communication. These results suggest that future weather displays should exploit the existing benefits of NEXRAD presentation for situation awareness while retaining the display structure and logic inherent in the onboard system.

Bliss, James P.↗
DOE OSTI2014

Assembly Level Modeling and Transportation Damage Prediction of Used Nuclear Fuel (UNF) Cladding

Under U.S. Nuclear Regulatory Commission (NRC) regulations, UNF must maintain its integrity in such a way that it can withstand the physical forces of handling and transportation associated with restaging the fuel and moving it to a different location such as an interim storage site, a geologic repository, or a treatment/recycling facility. Hence, understanding mechanical performance under cumulative loading stemming from normal conditions of storage (NCS), transfer from storage container to transport container if needed, and normal conditions of transport (NCT) is necessary as it establishes part of the safety basis via maintaining the fuel confining boundary (geometry), maintaining criticality safety, and is one of the critical components to the preservation of retrievability. An initial demonstration of modeling and simulation capabilities was performed as part of a collaborative effort between Pacific Northwest National Laboratory (PNNL), Sandia National Laboratory (SNL), Idaho National Laboratory (INL), Oak Ridge National Laboratory (ORNL), and the Transportation Technology Center Inc. (TTCI). This demonstration completed preliminary deterministic evaluations of moderate-to-high burnup UNF mechanical performance under NCS and NCT conditions. This paper focuses on work performed by PNNL on the assembly level modeling of a UNF assembly and fuel cladding damage predictions under NCT loads. The Finite Element (FE) model created for a 17 x 17 Pressurized Water Reactor (PWR) optimized fuel assembly (OFA) is discussed along with the communications to and from the fuel rod-level and cask-level models. Additionally, the methodology for determining cumulative damage is discussed including the 3000 mile damage prediction from a 10 second simulation. The damage results are shown for five shock and vibration broadened loading histories. It is found that predicted cladding strains were not large enough to cause structural failure, but cyclic strains roughly projected for the entire route were significant in some cases. The total damage from summation of the worst shock and vibration cases evaluated is approximately 18% of the expected fatigue limit. Therefore it is predicted that the fuel rods do not fail during NCT given the assumptions used throughout this initial demonstration.

used nuclear fuel, UNF, trasportation, damage, fue↗
NASA NTRS2016

Strategic Design of Long-Haul and Oceanic Aircraft Trajectories in Aviation Operations

Long-Haul Aircraft consume most of their fuel during the cruise phase of flight. The inefficiency in cruise flights compared to efficient routes varies is around 3 to 4. The efficiency of oceanic flights is low due to limited navigational and communication equipment, congestion and airspace restrictions. The availability of Automated Dependent Surveillance-Broadcast (ADS-B) and other improvements provides opportunity for better strategic planning of trajectories. Transatlantic flights between US and Europe constitute one of the busiest oceanic airspace regions in the world. This talk examines the benefits of a wind-optimal trajectory concept with a strategic de-confliction component compared to the current flight planning using the North Atlantic Tracks. The analysis is based on air traffic between US and Europe during July 2012. The potential fuel savings are in the range of (420-970) kg per flight for a Boeing 767-300, the most widely used aircraft between the city-pairs in this study. The talk also describes a global simulation of aviation operations combining flight plans and real air traffic data with historical commercial city-pair aircraft type and schedule data and global atmospheric data. The resulting capability extends the simulation and optimization functions of NASAs Future Air Traffic Management Concept Evaluation Tool (FACET) to global scale. This new capability is used to characterize the evolution of global air traffic, analyze fuel savings and seasonal variations in the long-haul wind-optimal traffic patterns in six major regions of the world.

strategic trajectory design↗
NASA NTRS2020

Distributed Spacecraft Autonomy (DSA): Development of Swarm Autonomy Capability and Scalability for Spacecraft

The Distributed Spacecraft Autonomy project is developing a suite of software tools that enable an operator to command and receive data from a swarm as a single entity, enable a swarm to autonomously coordinate its actions via distributed decision making and reactive closed-loop control, and model swarm behavior in the presence of anomalies or failures. Our use case is the mapping of the electron density of the ionosphere using radio tomography by coordinating the selection of appropriate GPS channels, and by recording Total Electron Count (TEC)measurements. DSA will be demonstrated on board the NASA Ames Starling mission a swarm of four small, LEO spacecraft, scheduled to launch in 2021. We will also perform a ground demonstration with simulated and hardware-in-the-loop elements, to validate the tools for controlling swarms of up to 100 assets.The capability to communicate autonomously between the swarm satellites is demonstrated via a sophisticated simulation architecture. Historical Plasma sphere TEC data obtained via dual-band Novatel GPS Receivers are utilized as a representative input data set for the swarm. The representative TEC data and GPS satellite observability information is fed to the autonomous software package in place of a true real-time ground data collection process. The swarm satellites actively share status updates amongst one another and utilize multi-agent decision making to optimally identify regions of interest in the TEC distribution. The software,aware of the bandwidth limitations of the swarm satellites, prioritizes explorative measurements,which define the range of observability for the satellites, as well as exploitative measurements,which focus on maximizing the observance potential of regions with prolonged, elevated TEC density. The science of this study can ultimately be used to determine the dynamics and coupling of Earth's magnetosphere, ionosphere, and atmosphere and their response to solar and terrestrial inputs. The findings can be applied to the imaging of critical, transient phenomena in the magnetosphere in later missions. Meanwhile, the swarm autonomy capabilities have far reaching potential in future satellite missions.As an experimental demonstration of the autonomous capabilities of the network, a message is first printed within a core Flight Executive (cFE) application. Two cFE applications that communicate with one another within the same core Flight System (cFS) are shown.Communication between mission applications on the internal cFE bus is extended to utilize Data Distribution Service (DDS) for vehicle-to-vehicle networking. The DDS middle ware provides reliable delivery, routing, and topic subscription features over User Data gram Protocol (UDP).Leveraging Linux containerization, a networked set of satellite instances are generated by script to simulate swarm behavior. Swarm commanding and synchronization through the network is demonstrated under various topologies and data-loss conditions. Finally, autonomous swarms calability from 2 satellites to 100 satellites is shown.

Fugate, Jason↗