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

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Energy Impact of Radiative Cooling Paints in Warehouses Under Various United States Climates

Although radiative cooling research is widely found in the literature, no comprehensive study has yet been conducted on the impact of novel radiant cooling (>0.91 reflectance) on the energy efficiency of warehouses. Here, in this work, we develop three building models based on a Department of Energy prototype warehouse model using trnsys, representing a typical warehouse with a black roof, a typical warehouse with a white roof, and a warehouse with novel radiative cooling (RC) paint on its roof. These models are run for 15 different cities, each representative of a different ASHRAE climate zone, to better understand the impact of RC in many different climates. It was found that an RC-coated roof in a warehouse could reduce the building's annual heating, ventilation, and air conditioning (HVAC) loads by up to 14.11 kWh/m 2 of the roof area compared to a black roof, resulting in a maximum reduction in energy costs of 0.55 $\$$/m 2 or $\$$2646/year for a large 4835 m 2 warehouse. Similarly, replacing the typical white roof coating with an RC coating could reduce the warehouse's energy consumption by up to 8.17 kWh/ m 2 of roof area, thus reducing energy costs by as much as 0.29 $\$$/m 2 or $\$$1386/year for a 4835 m 2 warehouse. In addition, applying RC paint to an unconditioned warehouse could reduce the building's ASHRAE Standard 55 indoor temperature exceedance by up to 1330 h/year compared to a black roof and up to 532 h/year compared to a white roof.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Non-Refrigerated Warehouse Design Guide [Slides]

Warehouses typically have a low energy use relative to their floor area. This make warehouses ideal to install solar panels and offset on-site energy use and have a surplus of energy if roof area is maximized. This surplus can be used to provide things like grid services or charge electric vehicle fleets. This document is intended to provide owners and operators of warehouse information on designing efficient/decarbonized warehouses and maximize on-site generation. The information here references outside publications to provide specific guidance, such as the ASHRAE Advanced Energy Design Guides, but tailors the information specifically to warehouses. This guide provides owners a better understanding of warehouse design as well as more specific information for themselves or outside designers to reference.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Improving the User Interface of the DeepLynx Data Warehouse

DeepLynx is an open-source ontology-based data warehouse created by INL to support the creation and life cycle of digital engineering projects, with a particular emphasis on digital twins [1]. Digital twins are systems that represent physical assets and process in a real-time digital environment [1]. Most well-known commercial data warehouses use Graphical User Interfaces (GUIs) for users to interact with their systems [3]. Limited publications have addressed the design of these interfaces and understanding of their target users. The current users and development team acknowledge the need to improve the current UI, not just for aesthetics but to improve functionality and workflow of DeepLynx. Traditional data warehouse users are developers, data scientists and business analysts [2]. DeepLynx users have a vast range of experience using data warehouses, and diverse roles, including engineers, scientists and management positions. Because there is a broader audience of target users for DeepLynx than a typical data warehouse, it is essential that DeepLynx has a useable and intuitive user interface. To achieve this the team performed human-computer interaction methods, including a Heuristic Evaluation of current UI using Neilsen’s Usability Heuristic, create personas based on current users by designing a user survey, data analysis and develop of personas. Followed by a redesign of the UI following using Neilsen’s Usability Heuristic and Norman’s Principles of Interactive Design in industry standard software Figma. Lastly a Heuristic Evaluation of new UI design, using Neilsen’s Usability Heuristic and User testing of redesign UI and have a group of users complete a Thinking Aloud Test of the new UI. Preliminary results of the Heuristic Evaluation of current UI arise issue with Consistency and Standards, Visibility of System Status, Match System and Real World and Recognition Rather than Recall. These issues were addressed in the proposed redesign by applying Neilsen’s Usability Heuristic and Norman’s Principles of Interactive Design. Next steps include formalized list of lessons learned and design implications for future publications.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2012

A Proposed Strategy for the U.S. to Develop and Maintain a Mainstream Capability Suite ("Warehouse") for Automated/Autonomous Rendezvous and Docking in Low Earth Orbit and Beyond

The ability of space assets to rendezvous and dock/capture/berth is a fundamental enabler for numerous classes of NASA fs missions, and is therefore an essential capability for the future of NASA. Mission classes include: ISS crew rotation, crewed exploration beyond low-Earth-orbit (LEO), on-orbit assembly, ISS cargo supply, crewed satellite servicing, robotic satellite servicing / debris mitigation, robotic sample return, and robotic small body (e.g. near-Earth object, NEO) proximity operations. For a variety of reasons to be described, NASA programs requiring Automated/Autonomous Rendezvous and Docking/Capture/Berthing (AR&D) capabilities are currently spending an order-of-magnitude more than necessary and taking twice as long as necessary to achieve their AR&D capability, "reinventing the wheel" for each program, and have fallen behind all of our foreign counterparts in AR&D technology (especially autonomy) in the process. To ensure future missions' reliability and crew safety (when applicable), to achieve the noted cost and schedule savings by eliminate costs of continually "reinventing the wheel ", the NASA AR&D Community of Practice (CoP) recommends NASA develop an AR&D Warehouse, detailed herein, which does not exist today. The term "warehouse" is used herein to refer to a toolbox or capability suite that has pre-integrated selectable supply-chain hardware and reusable software components that are considered ready-to-fly, low-risk, reliable, versatile, scalable, cost-effective, architecture and destination independent, that can be confidently utilized operationally on human spaceflight and robotic vehicles over a variety of mission classes and design reference missions, especially beyond LEO. The CoP also believes that it is imperative that NASA coordinate and integrate all current and proposed technology development activities into a cohesive cross-Agency strategy to produce and utilize this AR&D warehouse. An initial estimate indicates that if NASA strategically coordinates the development of a robust AR&D capability across the Agency, the cost of implementing AR&D on a spacecraft could be reduced from roughly $70M per mission to as low as $7M per mission, and the associated development time could be reduced from 4 years to 2 years, after the warehouse is completely developed. Table 1 shows the clear long-term benefits to the Agency in term of costs and schedules for various missions. (The methods used to arrive at the Table 1 numbers is presented in Appendices A and B.)

Krishnakumar, Kalmanje S.↗
NASA NTRS2021

Dendroarchaeological Analysis of the Terminal Warehouse in New York City Reveals A History of Long-Distance Timber Transport During the Gilded Age

The Gilded Age of the late 19th century marked a period of rapid development and urbanization in New York City, U.S. To accommodate the high demand in wood products during that time, the timbers used for development of the city were increasingly sourced from locations distant from the northeastern United States. The Terminal Warehouse in the Chelsea neighborhood of New York City was one of many large buildings erected during this period of city expansion, and is an important symbol of New York City commerce during the late 1800s. To determine the history and provenance of timbers used in the construction of the Terminal Warehouse, we used tree-ring analysis on longleaf pine (Pinus palustris Mill.) joists that were original to the building. The ring-width patterns on the joists cross dated well internally, suggesting a common origin of the sampled lumber. Further, our Terminal Warehouse tree-ring chronology (1512–1891 C.E.) correlated strongly with existing tree-ring chronologies from western/central Georgia and eastern Alabama, indicating that the timbers were extracted from this region of the southeastern United States. The provenancing and dating of the Terminal Warehouse timbers underscores the important role that southern pines played in the expansion and development of New York City during the Gilded Age.

Dendroprovenance↗
DOE OSTI2026

Radiative Cooling Paints: Application on Warehouses and Integration with Phase Change Materials

Despite extensive research on radiative cooling (RC), researchers are still working to understand its best implementation strategy and potential benefits. Understanding this could be an instrumental part of reducing building energy costs and combating climate change. In this work, we introduce two concepts to achieve this goal and broaden the application of RC paints. While building energy simulations for RC are common, most studies focus on single-layer paints in residential settings. Limited research exists on warehouses, and no literature has conducted multi-climate zone analyses or included RC technologies with >90% reflectance. As RC technology advances in efficiency, versatility, and affordability, large-scale simulations across diverse climates are crucial, particularly for warehouses as a passive indoor temperature control solution. Here, a TRNSYS-modeled single-story warehouse assesses the energy impact of BaSO4-based RC paints. Another under-explored RC application is its integration with phase change materials (PCMs), which provide thermal regulation via latent heat storage. Though RC and PCMs have been combined by placing PCMs atop, beneath, or within RC layers, studies focus on either experiments or modeling, with no validation between the two. Here, we develop a simple RC+PCM experimental and modeling setup, placing RC paint atop an aluminum cell filled with a Rubitherm PCM.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Sherlock Data Warehouse

Technical Interchange Meeting 2 of 2, with two linked events. Overall Purpose of the Technical Interchange Meeting was to facilitate collaboration on NAS data analytics between FAA and NASA teams, leveraging the great tool developed by NASA, Sherlock Data Warehouse. Conducted the two TIM events, next step is for the leadership to meet and discuss potential future collaborations. Purpose for Technical Interchange Meeting #2 (TIM 2o2); NASA presented data science related use-cases and applications where they have leveraged the NASA Sherlock Data Warehouse to address aviation transportation problems, with priority on aviation safety.

Two TIMs↗
NASA NTRS1982

Solar Space Heating for Warehouse--Kansas City, Kansas

New report describes warehouse/office building in Kansas City, Kansas which uses solar heating for warehouse portion and conventional heating and cooling for office portion. Building is divided into 20 equal units, each with its own solar-heating system. Modular design enables multiple units to be combined to form offices or warehouses of various sizes as required by tenants.

Source record↗
NASA NTRS1996

WATCHMAN: A Data Warehouse Intelligent Cache Manager

Data warehouses store large volumes of data which are used frequently by decision support applications. Such applications involve complex queries. Query performance in such an environment is critical because decision support applications often require interactive query response time. Because data warehouses are updated infrequently, it becomes possible to improve query performance by caching sets retrieved by queries in addition to query execution plans. In this paper we report on the design of an intelligent cache manager for sets retrieved by queries called WATCHMAN, which is particularly well suited for data warehousing environment. Our cache manager employs two novel, complementary algorithms for cache replacement and for cache admission. WATCHMAN aims at minimizing query response time and its cache replacement policy swaps out entire retrieved sets of queries instead of individual pages. The cache replacement and admission algorithms make use of a profit metric, which considers for each retrieved set its average rate of reference, its size, and execution cost of the associated query. We report on a performance evaluation based on the TPC-D and Set Query benchmarks. These experiments show that WATCHMAN achieves a substantial performance improvement in a decision support environment when compared to a traditional LRU replacement algorithm.

Scheuermann, Peter↗
NASA NTRS2019

Sherlock Data Warehouse

This slide deck provides an overview of the data and resources available in the Sherlock Data Warehouse. Sherlock was developed and is currently maintained by the Aviation Systems Division at NASA Ames Research Center. Sherlock contains a valuable collection of flight, air traffic management, and weather data. But Sherlock is not just a data archive. Sherlock also includes tools and resources to access, download, and visualize data, as well as resources to process the data. This overview summarizes Sherlock data sources, demonstrates data analytics and visualization with MicroStrategy, illustrates disparate data integration using the ATM Knowledge graph, and presents a machine learning use case using the Big Data system.

data warehouse↗
DOE OSTI2023

IceNet for FireBox - A Berkeley Warehouse-Scale Computer

Berkeley’s FireBox is a next-generation warehouse-scale computer (WSC) that utilizes the energy-efficiency and bandwidth density of integrated silicon-photonic interconnects to enable a new high-bandwidth and low-latency network fabric connecting thousands of compute nodes to petabytes of DRAM and Flash storage. The high bandwidth, low latency and high connectivity of FireBox’s WSC network fabric (IceNet) will enable dramatic improvements in the overall system energy efficiency enabling fine-grain power control on system resources (processors, links and memory/storage components). IceNet is a special 3-stage photonic Clos network architected to achieve ultra-low-latency connectivity between processor nodes and memory, drastically cutting down on the energy wasted in resource idling (processors and memory stalled due to pending network requests). This is achieved by integration of the first and last switch stages into processor/memory hub clients and by heavy over-provisioning of the high-radix middle switches (FlareSwitches). A key hardware component developed in this program is an active laser power management photonic integrated circuits called LightSpark. It interacts with the FlareSwitch and provides laser power to a subset of occupied switch ports, increasing the utilization of laser light in the photonic network by an order of magnitude. In addition to guiding the laser power where it is needed, the laser-power management module enables both wavelength and laser redundancy, significantly increasing the robustness of the system. The goal of the IceNet fabric is to enable communication between 1000s of processor nodes and PBs of memory/storage with <100ns latency, <10pJ/b wall-plug energy cost at multiple Pb/s of available connectivity bandwidth. These metrics represent two-orders of magnitude improvement with respect to the status of current data-center technology.

42 ENGINEERING↗
NASA NTRS1994

Controlling multiple security robots in a warehouse environment

The Naval Command Control and Ocean Surveillance Center (NCCOSC) has developed an architecture to provide coordinated control of multiple autonomous vehicles from a single host console. The multiple robot host architecture (MRHA) is a distributed multiprocessing system that can be expanded to accommodate as many as 32 robots. The initial application will employ eight Cybermotion K2A Navmaster robots configured as remote security platforms in support of the Mobile Detection Assessment and Response System (MDARS) Program. This paper discusses developmental testing of the MRHA in an operational warehouse environment, with two actual and four simulated robotic platforms.

Everett, H. R.↗
NASA NTRS2012

Security Data Warehouse Application

The Security Data Warehouse (SDW) is used to aggregate and correlate all JSC IT security data. This includes IT asset inventory such as operating systems and patch levels, users, user logins, remote access dial-in and VPN, and vulnerability tracking and reporting. The correlation of this data allows for an integrated understanding of current security issues and systems by providing this data in a format that associates it to an individual host. The cornerstone of the SDW is its unique host-mapping algorithm that has undergone extensive field tests, and provides a high degree of accuracy. The algorithm comprises two parts. The first part employs fuzzy logic to derive a best-guess host assignment using incomplete sensor data. The second part is logic to identify and correct errors in the database, based on subsequent, more complete data. Host records are automatically split or merged, as appropriate. The process had to be refined and thoroughly tested before the SDW deployment was feasible. Complexity was increased by adding the dimension of time. The SDW correlates all data with its relationship to time. This lends support to forensic investigations, audits, and overall situational awareness. Another important feature of the SDW architecture is that all of the underlying complexities of the data model and host-mapping algorithm are encapsulated in an easy-to-use and understandable Perl language Application Programming Interface (API). This allows the SDW to be quickly augmented with additional sensors using minimal coding and testing. It also supports rapid generation of ad hoc reports and integration with other information systems.

Vernon, Lynn R.↗
NASA NTRS2016

Supply Warehouse#3, SWMU 088 Operations, Maintenance, and Monitoring Report Kennedy Space Center, Florida

This document presents the findings, observations, and results associated with Operations, Maintenance, and Monitoring (OM&M) activities of Corrective Measures Implementation (CMI) activities conducted at Supply Warehouse #3 (SW3) located at John F. Kennedy Space Center (KSC), Florida from October 8, 2015, to September 12, 2016, and performance monitoring results for semi-annual sampling events conducted in March and September 2016. The primary objective of SW3 CMI is to actively decrease concentrations of trichloroethene (TCE) and vinyl chloride (VC) to less than Florida Department of Environmental Protection (FDEP) Natural Attenuation Default Concentrations (NADCs), and the secondary objective is to reduce TCE, cis-1,2-dichloroethene (cDCE), trans-1,2-dichloroethene (tDCE), 1,1-dichloroethene (11DCE), and VC concentrations to less than FDEP Groundwater Cleanup Target Levels (GCTLs). The SW3 facility has been designated Solid Waste Management Unit (SWMU) 088 under KSC's Resource Conservation and Recovery Act (RCRA) Corrective Action Program. Based on the results to date, the SW3 air sparging (AS) system is operating at or below the performance criteria as presented in the 2008 SW3 Corrective Measures Implementation (CMI) Work Plan and 2009 and 2012 CMI Work Plan Addenda. Since the start of AS system operations on December 19, 2012, through the September 2016 groundwater sampling event, TCE concentrations have decreased to less than the GCTL in all wells within the Active Remediation Zone (ARZ), and VC results remain less than NADC but greater than GCTL. Based on these results, team consensus was reached at the October 2016 KSC Remediation Team (KSCRT) meeting to continue AS system operations and semi-annual performance monitoring of volatile organic compounds in March 2017 at ten monitoring wells at select locations, and in September 2017 at four monitoring wells at select locations to reduce VC concentrations to below GCTL. Additionally, surface water samples will be collected at locations SW0001, SW0002, and SW0003 during both the March and September 2017 events. Team consensus was also reached at the October 2017 KSCRT meeting to continue with operation and maintenance (O&M) of the AS system at SW3.

REPORT↗
NASA NTRS2022

Greenhouse Gas Emission Estimations for 2016-2020 using the Sherlock Air Traffic Data Warehouse

Data and analyses are presented on the utilization of aircraft in the U.S. and the greenhouse gas emissions that they create. Commercial passenger and cargo aviation flight data, captured in the Sherlock data warehouse at NASA Ames over the five years from 2016 to 2020, is used to estimate the miles flown by major aircraft models. The estimates for aggregate annual number of flights are validated against data published by the Bureau of Transportation Statistics. The corresponding fuel usage is estimated using the International Civilian Aviation Organization (ICAO) fuel use tables and carbon dioxide emissions are calculated using a fuel-use multiplicative factor. A key conclusion of this analysis is that a small number of long-haul flights (with ranges greater than 2485 statute miles) create a disproportionately large fraction (30%) of annual total U.S. aviation-related carbon dioxide emissions, while a relatively large number of short flights (less than 311 statute miles) contribute a small net amount (less than 5%) of U.S. aviation-related carbon dioxide emissions. These U.S. results are consistent with a similar recent 2020 emissions study conducted by EUROCONTROL.

Emissions↗
NASA NTRS2023

Paint and Oil Locker, SWMU 067 Southern Treatment Area Air Sparge System Construction Completion and Performance Monitoring and Paint and Oil Locker, Northern Area (SWMU 067) and Supply Warehouse #3, SWMU 088 Long-Term Monitoring Report Kennedy Space Center, Florida

This Air Sparge (AS) System Construction Completion, Performance Monitoring, and Long-Term Monitoring (LTM) Report presents activities conducted at the Paint and Oil Locker (POL) (Solid Waste Management Unit [SWMU] 067) and Supply Warehouse #3 (SW3) (SWMU 088) sites located at the Kennedy Space Center (KSC), Florida. Activities include implementation and Year 1 (Quarters [Q] 1 through 4) and Q5 operation, maintenance, and monitoring (OM&M) activities and performance monitoring results for the AS Interim Measure (IM) in the POL Southern Treatment Area, LTM results for the POL Northern Area and SW3, and supplemental direct push technology (DPT) sampling at both sites to support the LTM and performance monitoring programs. The timeframe for activities included in this report extends from August 2019 to August 2022. The scope for these sites currently includes two main components, which are documented within this report: (1) LTM at SW3 and POL Northern Area where an AS system began operation at these sites in May 2009 and June 2013, respectively, and subsequently turned off for both sites in March 2018 (during the previous reporting period); and (2) Active AS operations and performance monitoring in the POL Southern Treatment Area where an AS system was installed and began operation in 2021. The AS IM in the POL Southern Treatment Area was implemented between 2019 and 2021 to treat a chlorinated solvent groundwater plume that resulted from historic operations supporting the National Aeronautics and Space Administration’s (NASA) Space Program. The objective of the AS IM is to remediate groundwater within the treatment zone to support transition to monitored natural attenuation (MNA). The overall Corrective Action objective is to reduce concentrations of trichloroethene (TCE), cis-1,2-dichloroethene (cDCE), trans-1,2- dichloroethene (tDCE), and vinyl chloride (VC) present in groundwater to levels below their respective State of Florida Groundwater Cleanup Target Levels (GCTLs). The AS IM was installed in the POL Southern Treatment Area to target the high concentration plume (HCP), which includes a source zone (SZ) area where TCE was found to exceed 11,000 micrograms per liter (µg/L), and extend to a depth of 30 feet below land surface (bls).

TCE↗