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All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Exploring Propulsion System Requirements for More and All-Electric Helicopters

Helicopters offer unique capabilities that are important for certain missions. More and all-electric propulsion systems for helicopters offer the potential for improved efficiency, reliability, vehicle and mission capabilities as well as reduced harmful emissions. To achieve these propulsion system-based benefits, the relevant requirements must be understood and developed for the various component, sub-component and ancillary systems of the overall propulsion system. Three representative helicopters were used to explore propulsion and overall vehicle and mission requirements. These vehicles varied from light utility (one to three occupants) to highly capable (three crew members plus ten passengers and cargo). Assuming 15 and 30 year technology availability, analytical models for electric system components were developed to understand component and ancillary requirements. Overall propulsion system characteristics were developed and used for vehicle sizing and mission analyses to understand the tradeoffs of component performance and weight, with increase in vehicle size and mission capability. Study results indicate that only the light utility vehicle retained significant payload for an arbitrary 100 nautical mile range assuming 15 year technology. Thirty year technology assumptions for battery energy storage are sufficient to enable some range and payload capabilities, but further improvements in energy density are required to maintain or exceed payload and range capabilities versus present systems. Hydrocarbon-fueled range extenders can be prudently used to recover range and payload deficiencies resulting from battery energy density limitations. Thermal loads for electric systems are low heat quality, but seem manageable. To realize the benefits from more and all-electric systems, technology goals must be achieved, as well as vehicles, missions and systems identified that are best suited to take advantage of their unique characteristics.

mission analysis↗
NASA NTRS2015

Exploring Propulsion System Requirements for More and All-Electric Helicopters

Helicopters offer unique capabilities that are important for certain missions. More and all-electric propulsion systems for helicopters offer the potential for improved efficiency, reliability, vehicle and mission capabilities as well as reduced harmful emissions. To achieve these propulsion system-based benefits, the relevant requirements must be understood and developed for the various component, sub-component and ancillary systems of the overall propulsion system. Three representative helicopters were used to explore propulsion and overall vehicle and mission requirements. These vehicles varied from light utility (one to three occupants) to highly capable (three crew members plus ten passengers and cargo). Assuming 15 and 30 year technology availability, analytical models for electric system components were developed to understand component and ancillary requirements. Overall propulsion system characteristics were developed and used for vehicle sizing and mission analyses to understand the tradeoffs of component performance and weight, with increase in vehicle size and mission capability. Study results indicate that only the light utility vehicle retained significant payload for an arbitrary 100 nautical mile range assuming 15 year technology. Thirty year technology assumptions for battery energy storage are sufficient to enable some range and payload capabilities, but further improvements in energy density are required to maintain or exceed payload and range capabilities versus present systems. Hydrocarbon-fueled range extenders can be prudently used to recover range and payload deficiencies resulting from battery energy density limitations. Thermal loads for electric systems are low heat quality, but seem manageable. To realize the benefits from more and all-electric systems, technology goals must be achieved, as well as identify vehicles, missions and systems that are best suited to take advantage of their unique characteristics.

gearbox↗
DOE OSTI2025

Fabrication and Testing of Solid-Solution Strengthened Corrosion Resistant Alloys For Service in Molten Fluoride Environments

The demand for higher system thermal efficiencies requires the operation of power generation cycles and heat conversion systems at progressively higher temperatures. As the system operating temperature increases, existing materials may not provide adequate mechanical properties or environmental compatibility or both. There is an increasing commercial interest in the development and deployment of liquid-fueled Molten Salt Reactors (MSRs). Hastelloy®N, the highest performing candidate MSR structural alloy, is not capable of operations at temperatures above 700°C, thus limiting the performance of these systems. Using an Integrated Computational Materials Engineering (ICME)-approach and small laboratory scale heats, ORNL developed a class of patented alloys covered by U.S. Patent 9, 435, 011 B2, “Creep-resistant, Cobalt-free alloys for high temperature, liquid-salt heat exchanger systems,” similar to Hastelloy®N in that they are primarily solid solution strengthened. In contrast to precipitation strengthened alloys, the microstructure of solid solution alloys and hence the high temperature mechanical properties are stable for extended periods of time allowing long reactor operating life. The new alloys have shown to possess good resistance to liquid fluorides at temperatures up to 850°C and have significantly improved creep properties when compared to Hastelloy®N. The purpose of the CRADA project was for ORNL to collaborate with Haynes International- a materials producer, MetalTek International- a foundry, and Kairos Power – an advanced reactor developer – to scale-up selected alloys, evaluate their properties, and identify one solid solution strengthened alloy that can meet the property requirements for the reactor being developed by Kairos Power and other similar liquid fluoride-salt cooled reactors. As part of the project, eight alloys were down-selected and fabricated in larger industrial scale heats by Haynes International. Resistance to molten salt was evaluated in flowing FLiNaK and FLiBe by Kairos Power using their Rotating Cage Loop (RCL) system. Accounting for iron deposition during these tests, the new alloys displayed very low net mass change showing excellent corrosion performance in molten salt. Creep properties evaluated at ORNL were found to be better than that of Hastelloy®N and 316 stainless steel. Long-term stabilities of the alloys evaluated by Haynes International showed that these alloys have excellent thermal stability in the temperature range 704.4-815.6°C, with the change in strength and ductility being less than 10-15% after a 4000-hour exposure at 815.6°C. Autogenously Gas Tungsten Arc Welding (GTAW) welded samples showed less than 10% change in yield strength / ultimate tensile strength / total elongation compared to the basemetal, indicating that the alloys have excellent weldability. Three parts were successfully investment-cast using one alloy with very little voiding showing feasibility of fabricating parts using the casting process. This project enabled extensive interaction between the material producer Haynes International, casting supplier MetalTek, and reactor developer Kairos Power. This facilitated testing of materials and components produced using the newly developed alloys by the end-user. This allowed the generation of critical dataset required for down-selection of a few promising alloys for further development. This data is also currently being shared with other reactor designers for them to evaluate the suitability of this alloy for their reactor design. The availability of this alloy will ultimately enable the design and development and deployment of MSRs with increased temperature of operation and thus, improved efficiencies.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Fabrication and Testing of Solid-Solution Strengthened Corrosion Resistant Alloys For Service in Molten Fluoride Environments

The demand for higher system thermal efficiencies requires the operation of power generation cycles and heat conversion systems at progressively higher temperatures. As the system operating temperature increases, existing materials may not provide adequate mechanical properties or environmental compatibility or both. There is an increasing commercial interest in the development and deployment of liquid-fueled Molten Salt Reactors (MSRs). Hastelloy®N, the highest performing candidate MSR structural alloy, is not capable of operations at temperatures above 700°C, thus limiting the performance of these systems. Using an Integrated Computational Materials Engineering (ICME)-approach and small laboratory scale heats, ORNL developed a class of patented alloys covered by U.S. Patent 9,435,011 B2, “Creep-resistant, Cobalt-free alloys for high temperature, liquid-salt heat exchanger systems,” similar to Hastelloy®N in that they are primarily solid solution strengthened. In contrast to precipitation strengthened alloys, the microstructure of solid solution alloys and hence the high temperature mechanical properties are stable for extended periods of time allowing long reactor operating life. The new alloys have shown to possess good resistance to liquid fluorides at temperatures up to 850°C and have significantly improved creep properties when compared to Hastelloy®N. The purpose of the CRADA project was for ORNL to collaborate with Haynes International- a materials producer, MetalTek International- a foundry, and Kairos Power – an advanced reactor developer – to scale-up selected alloys, evaluate their properties, and identify one solid solution strengthened alloy that can meet the property requirements for the reactor being developed by Kairos Power and other similar liquid fluoride-salt cooled reactors. As part of the project, eight alloys were down-selected and fabricated in larger industrial scale heats by Haynes International. Resistance to molten salt was evaluated in flowing FLiNaK and FLiBe by Kairos Power using their Rotating Cage Loop (RCL) system. Accounting for iron deposition during these tests, the new alloys displayed very low net mass change showing excellent corrosion performance in molten salt. Creep properties evaluated at ORNL were found to be better than that of Hastelloy®N and 316 stainless steel. Long-term stabilities of the alloys evaluated by Haynes International showed that these alloys have excellent thermal stability in the temperature range 704.4-815.6°C, with the change in strength and ductility being less than 10-15% after a 4000-hour exposure at 815.6°C. Autogenously Gas Tungsten Arc Welding (GTAW) welded samples showed less than 10% change in yield strength / ultimate tensile strength / total elongation compared to the basemetal, indicating that the alloys have excellent weldability. Three parts were successfully investment-cast using one alloy with very little voiding showing feasibility of fabricating parts using the casting process. This project enabled extensive interaction between the material producer Haynes International, casting supplier MetalTek, and reactor developer Kairos Power. This facilitated testing of materials and components produced using the newly developed alloys by the end-user. This allowed the generation of critical dataset required for down-selection of a few promising alloys for further development. This data is also currently being shared with other reactor designers for them to evaluate the suitability of this alloy for their reactor design. The availability of this alloy will ultimately enable the design and development and deployment of MSRs with increased temperature of operation and thus, improved efficiencies.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Characterization of Fe-6Si Soft Magnetic Alloy Produced by Laser-Directed Energy Deposition Additive Manufacturing

Abstract Commercial electrical steels, Fe-Si alloys with < 4 wt.% Si, are inexpensive and efficient materials for electrical power conversion. Further efficiency improvements require increasing the silicon concentration to 6 wt.%, at which point the material becomes brittle and difficult to form by conventional rolling and sheet fabrication methods. Additive manufacturing stands to overcome challenges with commercial manufacturing techniques by leveraging near-net-shape fabrication. The wide array of process conditions provides additive manufacturing with increased flexibility, enabling control over the microstructure and mechanical properties. This work explores the microstructures and magnetic properties of ring-shaped Fe-Si alloys produced using concentric and cross-hatch tool paths on a laser-directed energy deposition additive manufacturing system. Concentric-built samples exhibit elongated grain structures while cross-hatch-built samples comprise lower aspect ratio grain structures. Thermal finite element analysis simulations model the stress conditions produced by the different scan path geometries. Microhardness measurements probe the mechanical properties as a function of anneal temperature, providing a qualitative understanding of the intergranular defect density. Soft magnetic properties measured under quasistatic and AC conditions show frequency- and microstructure-dependent coercivity and permeability. Finally, analysis of the core loss quantifies how the build strategies and thermal treatments influence efficiency in electrical power conversion applications. Understanding the influences of scan path geometry and thermal treatment provides a pathway towards application of additively manufactured soft magnetic materials.

Adamczyk, Jesse M.↗
DOE OSTI2024

Low-Cost, High-Performance Carbon Fiber for Compressed Natural Gas Storage Tanks (Final Technical Report – Down Select Report)

The aim of this project is to reduce the cost of Type IV, carbon fiber (CF) composite overwrap compressed gas storage tanks by reducing the cost of CF and CF composites. The project team worked to reduce the cost of CF by exploring and testing opportunities for a low-cost alternative precursor material for CF production to supplant market-dominant and costly polyacrylonitrile (PAN). Concurrently, the team aimed to reduce the cost of the tanks at the composite level by improving the interfacial adhesion between the fibers and the matrix resin through the incorporation of low-cost nanoparticles recycled from waste materials, which would reduce the volume of costly CF required to achieve the same tank performance. At the end of the first year, the project team selected mesophase pitch as the primary precursor candidate from a field of materials based on the superior mechanical performance and cost-saving potential. During the second year, the team produced CFs derived from mesophase pitch achieving an average tensile strength of 365.6 ksi and average tensile modulus of 40.74 Msi. Facility availability for spinning and converting these fibers at greater scale has hindered scale-up demonstration, but the team has identified opportunities to conduct this work in the near term. Cost modeling shows that these mesophase pitch-derived CFs can be up to 40% less expensive than PAN-derived CFs due to the lower cost of the feedstock material, higher throughput, greater conversion yield, and lower cost spinning method and compared to PAN. Additionally, the team has demonstrated at lab-scale that nanoparticle coating CFs can significantly increase the interfacial shear strength and load transfer efficiency of CFs in a matrix. Single filament pull-out testing showed a 27% average increase in max interfacial shear strength due to this coating. A continuous method of applying these coatings to a tow of CF has been developed for scale-up. 26 m tows of coated CFs were produced using this system and formed into composite ring samples for ASTM ring burst testing. Issues with the testing protocol have limited assessment of these results. A prototype Type IV tank was designed to meet ANSI HGV2 standards, and the design criteria set out by DOE, using the CF properties developed by the team paired with a proprietary resin matrix, a polyamide liner, and aluminum end bosses. The tank weighs 153.1 kg and with a total capacity of 5.8 kg H2 (5.6 kg usable), which yields a gravimetric capacity of 1.17 kWh/kg. Cost modeling predicts that the tank will have a projected cost of $15.73/kWh. Tank performance modeling does not include considerations for fiber-matrix load transfer efficiency improvements offered by nanoparticle coating method.

08 HYDROGEN↗
NASA NTRSDate not supplied

A Wall-Distance Method for Turbulence Modeling

The distance from a grid point to the closest wall surface, wall distance, is a funda- mental quantity in turbulence modeling. Efficiency of wall-distance calculations has become more critical as the size of computational grids has significantly increased in recent years. This paper reports on an initial implementation of a new search-based wall-distance method that is suitable for general unstructured computational fluid dynamics (CFD) grids and tailored for requirements specific for turbulence modeling. The method represents a two-step approach to calculate the wall distance. In the first step, the wall distance is approximated for each grid point as the minimum distance from this point to a vertex of a triangular face at the wall. The point-to-vertex distance calculation is relatively inexpensive but may lead to a significant error in the wall-distance ap- proximation, especially for grid points near the wall. In the second step, for grid points located within a predefined distance ( threshold ) from the wall, the wall distance is computed as the minimum distance to wall faces. As a result, the wall distance is exact for all grid points within the threshold. This two-step approach reduces the computational cost yet achieves high and controllable accuracy in the evaluation of the wall distance. Algorithmic enhancements are presented to improve efficiency of wall-distance computations. Comprehensive assessment of the new method is reported for large-scale unstructured CFD grids generated for the Fifth AIAA CFD High-Lift Prediction Workshop. The performance of the new wall-distance method compares favorably with performance of two established methods implemented in high-performance CFD codes.

Wall Distance↗
DOE OSTI2025

Current state and future projections of drying processes in the US food and pulp and paper sectors: Energy, economic, and environmental assessment

The pulp and paper (P/P) and food sectors are the third- and fifth-largest industrial energy consumers in the United States, with total on-site energy consumption of 2,039 TBtu and 1,144 TBtu, respectively. Thermal drying processes for moisture removal, which are energy-intensive, play a critical role in both industries. This study is the first to evaluate state- and national-level US drying energy demand for these sectors from 2020 to 2050. To complete this evaluation, we developed a thermodynamic modeling framework integrated with economic and environmental models to compute product-specific drying energy intensity and estimate the sector-specific costs and emissions profiles associated with drying operations. The model-predicted energy intensity was validated against the literature. Using current and projected annual production volumes in these sectors, we estimated total drying energy use. Results indicate that drying accounts for 22 % of total energy consumption in the P/P sector and 10 % in the food sector. The estimated annual energy cost (2020) to operate thermal dryers is $\$$919 M in the P/P sector and $\$$417 M in the food sector. Additionally, drying contributes to 25 % of total CO 2 e emissions in the P/P sector (including biogenic) and 15 % of emissions in the food sector. Regional performance shows that the Southern US is the leading energy consumer for P/P drying, whereas the Midwest leads in food drying. This study presents both potential solutions to enhance drying efficiency and barriers to implementation. Energy efficiency improvements, low-carbon fuels, and electrification are discussed as key pathways for reducing costs and optimizing industrial drying processes.

3E analysis↗
DOE OSTI2020

Vision-Guided Automation and Assistance

Robotic automation and assistance is an excellent way to increase efficiency and safety when working in a potentially hazardous workspace. However, many traditional automation approaches rely on the precise placement of items to be manipulated. The scope of such automated tasks is also limited to the manipulation of one type of object since there is no way to distinguish between different objects. The addition of a vision pipeline, where robot vision is used to localize and recognize objects, can allow the robot to perform more complex tasks in a variable workspace. In my vision pipeline, a depth camera is used to generate a 3D point cloud of the workspace. Objects to be manipulated are isolated in the point cloud by filtering out shared surfaces and using Euclidean cluster extraction to group clusters of points. The locations of the objects are then estimated from the point cloud of the isolated objects. The localization of objects with robot vision allows for variable workspaces, reducing the overhead associated with requiring all objects to be precisely placed in the workspace. For object recognition, deep learning is used to train a neural network that classifies objects from the raw point clouds. More complex tasks that require multiple objects to be manipulated differently can be achieved through the vision pipeline. Through its ability to visualize the workspace, robot vision greatly improves efficiency and safety of automated and assistive tasks.

42 ENGINEERING↗
NASA NTRS2014

NASA's Advanced Environmental Barrier Coatings Development for SiC/SiC Ceramic Matrix Composites: Understanding Calcium Magnesium Alumino-Silicate (CMAS) Degradations and Resistance

Environmental barrier coatings (EBCs) and SiCSiC ceramic matrix composites (CMCs) systems will play a crucial role in next generation turbine engines for hot-section component applications because of their ability to significantly increase engine operating temperatures with improved efficiency, reduce engine weight and cooling requirements. The development of prime-reliant environmental barrier coatings is essential to the viability and reliability of the envisioned CMC engine component applications, ensuring integrated EBC-CMC system durability and designs are achievable for successful applications of the game-changing component technologies and lifing methodologies.This paper will emphasize recent NASA environmental barrier coating developments for SiCSiC turbine airfoil components, utilizing advanced coating compositions, state-of-the-art processing methods, and combined mechanical and environment testing and durability evaluations. The coating-CMC degradations in the engine fatigue-creep and operating environments are particularly complex; one of the important coating development aspects is to better understand engine environmental interactions and coating life debits, and we have particularly addressed the effect of Calcium-Magnesium-Alumino-Silicate (CMAS) from road sand or volcano-ash deposits on the durability of the environmental barrier coating systems, and how the temperature capability, stability and cyclic life of the candidate rare earth oxide and silicate coating systems will be impacted in the presence of the CMAS at high temperatures and under simulated heat flux conditions. Advanced environmental barrier coating systems, including HfO2-Si with rare earth dopant based bond coat systems, will be discussed for the performance improvements to achieve better temperature capability and CMAS resistance for future engine operating conditions.

Environmental barrier coatings↗
DOE OSTI2020

Performance of a CO 2 sorbent for indoor air cleaning applications: Effects of environmental conditions, sorbent aging, and adsorption of co-occurring formaldehyde

Indoor air cleaning systems that incorporate CO 2 sorbent materials enable HVAC load shifting and efficiency improvements. This study developed a bench-scale experimental system to evaluate the performance of a sorbent under controlled operation conditions. A thermostatic holder containing 3.15 g sorbent was connected to a manifold that delivered CO 2 -enriched air at a known temperature and relative humidity (RH). The air stream was also enriched with 0.8-2.1 ppm formaldehyde. The CO 2 concentration was monitored in real-time upstream and downstream of the sorbent, and integrated formaldehyde samples were collected at different times using DNPH-coated silica cartridges. Sorbent regeneration was carried out by circulating clean air in countercurrent. Almost 200 loading/regeneration cycles were performed in the span of 17 months, from which 104 were carried out at reference test conditions defined by loading with air at 25°C, 38% RH, and 1000 ppm CO 2 , and regenerating with air at 80°C, 3% RH and 400 ppm CO 2 . The working capacity decreased slightly from 43-44 mg CO 2 per g sorbent to 39-40 mg per g over the 17 months. The capacity increased with lower loading temperature (in the range 15-35°C) and higher regeneration temperature, between 40 and 80°C. The CO 2 capacity was not sensitive to the moisture content in the range 6-9 g/m 3 , and decreased slightly when dry air was used. Loading isothermal breakthrough curves were fitted to three simple adsorption models, verifying that pseudo-first-order kinetics appropriately describes the adsorption process. The model predicted that equilibrium capacities decreased with increasing temperature from 15 to 35°C, while adsorption rate constants slightly increased. The formaldehyde adsorption efficiency was 80%-99% in different cycles, corresponding to an average capacity of 86 ± 36 µg/g. Formaldehyde was not quantitatively released during regeneration, but its accumulation on the sorbent did not affect CO 2 adsorption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Machine Learning-Based Process Control for Injection Molding of Recycled Polypropylene

The increased interest in artificial intelligence in manufacturing has driven the adoption of machine learning to optimize processes and improve efficiency. A key challenge in injection molding is the variability of recycled materials, which affects part quality and processing stability. This study presents a novel closed-loop process control approach for injection molding, leveraging machine learning to adaptively predict processing inputs and quality outcomes. The methodology was tested on five blends of recycled polypropylene (rPP), using artificial neural networks (ANNs), linear regression, and polynomial regression to model the relationships between material properties and process parameters. The dataset was split 80/20 into training and testing sets. The ANN model was implemented using TensorFlow and Keras, with six hidden layers of 32 neurons per layer, ReLU activation, and an Adam optimizer. Empirical tuning and early stopping were used to optimize performance and prevent overfitting. Predictions were evaluated based on mean absolute error (MAE), mean squared error (MSE), and percentage error. The results showed that yield stress, ultimate elongation, and part weight were accurately predicted within a 5% error for linear and polynomial regression models and within a 10% error for the ANN. However, modulus predictions were less reliable, with errors of ~11% for ANN and linear regression and ~40% for polynomial regression, reflecting the inherent variability of this property in rPP blends. Predictions of processing inputs had errors ranging from 3% to 25%, depending on the model and response variable. No single modeling approach was consistently superior across all responses, highlighting the complexity of the relationship between material properties, process parameters, and quality metrics. Overall, the work demonstrates that closed-loop process control, powered by machine learning, can effectively predict key quality parameters in injection molding of recycled materials. The proposed approach can improve process stability and material utilization, facilitating increased adoption of sustainable materials.

Krantz, Joshua↗
DOE OSTI2025

Alaska's Rural Building Stock: a Validation Study Using ResStock and Field Data

The availability of accurate national data on demographics, building stock, and energy use is vital for modeling residential buildings and evaluating decarbonization strategies. However, rural and Indigenous populations, including those in rural Alaska, are typically underrepresented in these datasets. These communities face unique challenges due to their remote locations, severe weather conditions, and limited access to resources, resulting in high energy burden. This report examines how rural Alaskan communities are underrepresented in the ResStock housing model and highlights the need for improved data to address their unique housing and energy challenges. Thus, this report examines the representation of rural Alaskan communities within the national housing stock model, ResStock. A validation study was conducted, considering ResStock, Field Data and Aerial and 3D-view data collection (A3DDC) datasets. The validation process started by using the down selecting approach on the ResStock building stock dataset. For the purpose of this study, only the rural Alaska Boroughs and Census areas located in ASHRAE IECC Climate Zone 8 were considered to ensure a more accurate and fair comparison with the field data, which was collected in rural areas located in climate zone 8, specifically within the Nome Census area. While ResStock may accurately represent several characteristics of the building stock for rural Alaska, some differences between modeled, field data, and aerial and 3D-view data collection datasets were identified. The following building characteristics have a high impact on modeled energy consumption and demonstrated large differences: Revisit heating setpoints and consider a substantially higher setpoint distribution, it could potentially address "missing loads" if this is the case. Develop and include Toyo heating in future modeling for ResStock and EnergyPlus. Remove natural gas as a water heater fuel type outside of North Slope County. Foundation type updated to have more crawlspaces rather than basements. Infiltration rates need reexamination for a larger distribution toward higher infiltration rates. Include more vinyl and less brick in exterior wall type and revise wall color for greater proportion of light rather than dark color. Roof material revised from majority shingles to majority metal. Update number of occupants to higher number of occupant count. Building orientation represents a higher proportion of south facing buildings rather than relatively equal. The findings suggest that updating ResStock's probability logic could better represent rural Alaskan buildings. ResStock can be utilized to identify the best upgrades or energy efficiency and energy efficiency improvements, helping community leaders in making more informed decisions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Development and Implementation of Fault-Correction Algorithms in Fault Detection and Diagnostics Tools

A fault detection and diagnostics (FDD) tool is a type of energy management and information system that continuously identifies the presence of faults and efficiency improvement opportunities through a one-way interface to the building automation system and the application of automated analytics. Building operators on the leading edge of technology adoption use FDD tools to enable median whole-building portfolio savings of 8%. Although FDD tools can inform operators of operational faults, currently an action is always required to correct the faults to generate energy savings. A subset of faults, however, such as biased sensors, can be addressed automatically, eliminating the need for staff intervention. Automating this fault “correction” can significantly increase the savings generated by FDD tools and reduce the reliance on human intervention. Doing so is expected to advance the usability and technical and economic performance of FDD technologies. This paper presents the development of nine innovative fault auto-correction algorithms for Heating, Ventilation, and Air Conditioning pi(HVAC) systems. When the auto-correction routine is triggered, it overwrites control setpoints or other variables to implement the intended changes. It also discusses the implementation of the auto-correction algorithms in commercial FDD software products, the integration of these strategies with building automation systems and their preliminary testing.

field testing↗
NASA NTRS2005

Using Cloud-to-Ground Lightning Climatologies to Initialize Gridded Lightning Threat Forecasts for East Central Florida

Each morning, the forecasters at the National Weather Service in Melbourn, FL (NWS MLB) produce an experimental cloud-to-ground (CG) lightning threat index map for their county warning area (CWA) that is posted to their web site (http://www.srh.weather.gov/mlb/ghwo/lightning.shtml) . Given the hazardous nature of lightning in central Florida, especially during the warm season months of May-September, these maps help users factor the threat of lightning, relative to their location, into their daily plans. The maps are color-coded in five levels from Very Low to Extreme, with threat level definitions based on the probability of lightning occurrence and the expected amount of CG activity. On a day in which thunderstorms are expected, there are typically two or more threat levels depicted spatially across the CWA. The locations of relative lightning threat maxima and minima often depend on the position and orientation of the low-level ridge axis, forecast propagation and interaction of sea/lake/outflow boundaries, expected evolution of moisture and stability fields, and other factors that can influence the spatial distribution of thunderstorms over the CWA. The lightning threat index maps are issued for the 24-hour period beginning at 1200 UTC (0700 AM EST) each day with a grid resolution of 5 km x 5 km. Product preparation is performed on the AWIPS Graphical Forecast Editor (GFE), which is the standard NWS platform for graphical editing. Currently, the forecasters create each map manually, starting with a blank map. To improve efficiency of the forecast process, NWS MLB requested that the Applied Meteorology Unit (AMU) create gridded warm season lightning climatologies that could be used as first-guess inputs to initialize lightning threat index maps. The gridded values requested included CG strike densities and frequency of occurrence stratified by synoptic-scale flow regime. The intent is to increase consistency between forecasters while enabling them to focus on the mesoscale detail of the forecast, ultimately benefiting the end-users of the product. Several studies took place at the Florida State University (FSU) and NWS Tallahassee (TAE) for which they created daily flow regimes using Florida 1200 UTC synoptic soundings and CG strike densities from National Lightning Detection Network (NLDN) data. The densities were created on a 2.5 km x 2.5 km grid for every hour of every day during the warm seasons in the years 1989-2004. The grids encompass an area that includes the entire state of Florida and adjacent Atlantic and Gulf of Mexico waters. Personnel at the two organizations provided this data and supporting software for the work performed by the AMU. The densities were first stratified by flow regime, then by time in 1-, 3-, 6-, 12-, and 24-hour increments while maintaining the 2.5 km x 2.5 km grid resolution. A CG frequency of occurrence was calculated for each stratification and grid box by counting the number of days with lightning and dividing by the total number of days in the data set. New CG strike densities were calculated for each stratification and grid box by summing the strike number values over all warm seasons, then normalized by dividing the summed values by the number of lightning days. This makes the densities conditional on whether lightning occurred. The frequency climatology values will be used by forecasters as proxy inputs for lightning prObability, while the density climatology values will be used for CG amount. In addition to the benefits outlined above, these climatologies will provide improved temporal and spatial resolution, expansion of the lightning threat area to include adjacent coastal waters, and potential to extend the forecast to include the day-2 period. This presentation will describe the lightning threat index map, discuss the work done to create the maps initialized with climatological guidance, and show examples of the climatological CG lightning densities and frequencies of occurren based on flow regime.

Lambert, Winnie↗
DOE OSTI2023

Key Considerations in Assessing the Safety and Performance of Camera-Based Mirror Systems

Camera-based mirror systems (CBMSs) are a relatively new technology in the automotive industry, and much of the United States’ medium- and heavy-duty commercial fleet has been reluctant to convert from standard glass, or “west coast”, mirrors to CBMSs. CBMSs have the potential to reduce the number of truck and passenger vehicle incidents, improving overall fleet safety. CBMSs also have the potential to improve operational efficiency by improving aerodynamics and reducing drag, resulting in better fuel economy, and improving maneuverability. Improvements in overall safety are also possible; the field of view for the driver is potentially 360° with the addition of trailer cameras, allowing for visibility of the rear of the trailer and the front of the truck. These potential improvements seem promising, but the literature on driver surveys clearly shows that there is reluctance to adopt this technology for many reasons. Additionally, more robust testing in the laboratory and in the field is necessary to determine whether CBMSs are adequate to replace standard mirrors on trucks. This analysis provides an overview of key research questions for CBMS testing based on the current literature on the topic (surveys, standards, and previous testing). The purpose of this analysis is to serve as guidance in developing further testing of CBMSs, especially testing involving human subjects.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Atomic Gradient Structure Alters Electronic Structure in 3D across the Bulk and Enhances Photoactivity

Abstract Understanding structure–function relationships enables the design of materials with tailored functionalities. The long‐standing challenge is to design materials with high active volume to improve efficiency. Tailored grain boundaries and lattice defects are traditionally used to tune the electronic structure near interfaces or defects to promote electron and hole separation. However, the active volume of point defect sites or interfaces in these traditional photocatalysts is extremely low. This study reports a structure with continuous atomic positional deformation across the bulk, altering the electronic structure in 3D and creating a significantly higher active volume. Such a structure in anatase is obtained and tuned by phase transformation during the heating process. Transmission electron microscopy and density functional theory results reveal that atomic deformations result in continuous band bending across the particles, facilitating electron–hole separation, inhibiting their recombination, and inducing dramatically enhanced photoactivity. These findings enable a different materials design paradigm that can potentially be harnessed for a broad range of applications.

Ren, Peng↗