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DOE OSTI2025

HPC Campaign Management: Remote data access with user-defined error bound using ADIOS and ZFP

Remote access to large-scale scientific datasets, like those generated by combustion simulations or other high-performance computing (HPC) applications, presents a significant challenge. Downloading entire datasets is often impractical due to their size and the bandwidth limitations of typical networks. To address this challenge, we propose a novel approach that enables efficient remote access to large datasets distributed across multiple facilities. Our method enables technologies to download only the data values of a select variable, in a select region of interest, to a user-defined accuracy. For this purpose, we extended the ADIOS IO library to provide read functions with user-defined accuracy, a remote data server that understands multidimensional selections of specific variables, steps and accuracy from an ADIOS dataset, and which uses lossy compression on the remote site to reduce the data to be transferred back to the client. In addition, our extension of the ADIOS library collects metadata from multiple datasets in small files called Campaign Archives, which can be shared among project participants on any HPC, cloud or laptop, and which can easily facilitate the discovery of content and pointers to the data location as well as remote access to the data by local tools as if data was local. This feature called Campaign Management, enables a group of scientists to manage related datasets stored in multiple files, across multiple facilities as if it was in a single file/database. We demonstrate the effectiveness of our approach using a 1.5 TB dataset from the S3D combustion simulation on Frontier at the Oak Ridge Leadership Facility. Even a single variable from this dataset, at 64 GB, is too large to be processed on a standard laptop. We show two different reading patterns for 2D plots and 3D visualization, with careful settings that a scientist studying combustion data would do and show that running the same Python scripts on Frontier directly takes comparable time than running them on the local laptop with remote access to the data on Frontier.

Podhorszki, Norbert [ORNL] (ORCID:000000019647542X↗

NASA NTRS1992

Multi-resolution processing for fractal analysis of airborne remotely sensed data

Fractal geometry is increasingly becoming a useful tool for modeling natural phenomenon. As an alternative to Euclidean concepts, fractals allow for a more accurate representation of the nature of complexity in natural boundaries and surfaces. Since they are characterized by self-similarity, an ideal fractal surface is scale-independent; i.e. at different scales a fractal surface looks the same. This is not exactly true for natural surfaces. When viewed at different spatial resolutions parts of natural surfaces look alike in a statistical manner and only for a limited range of scales. Images acquired by NASA's Thermal Infrared Multispectral Scanner are used to compute the fractal dimension as a function of spatial resolution. Three methods are used to determine the fractal dimension - Schelberg's line-divider method, the variogram method, and the triangular prism method. A description of these methods and the results of applying these methods to a remotely-sensed image is also presented. Five flights were flown in succession at altitudes of 2 km (low), 6 km (mid), 12 km (high), and then back again at 6 km and 2 km. The area selected was the Ross Barnett reservoir near Jackson, Mississippi. The mission was flown during the predawn hours of 1 Feb. 1992. Radiosonde data was collected for that duration to profile the characteristics of the atmosphere. This corresponds to 3 different pixel sizes - 5m, 15m, and 30m. After, simulating different spatial sampling intervals within the same image for each of the 3 image sets, the results are cross-correlated to compare the extent of detail and complexity that is obtained when data is taken at lower spatial intervals.

Jaggi, S.↗

NASA NTRS2011

Bringing Together Users and Developers of Forest Biomass Maps

Brown, Molly E.↗

NASA NTRS2012

Bringing Together Users and Developers of Forest Biomass Maps

Forests store carbon and thus represent important sinks for atmospheric carbon dioxide. Reducing uncertainty in current estimates of the amount of carbon in standing forests will improve precision of estimates of anthropogenic contributions to carbon dioxide in the atmosphere due to deforestation. Although satellite remote sensing has long been an important tool for mapping land cover, until recently aboveground forest biomass estimates have relied mostly on systematic ground sampling of forests. In alignment with fiscal year 2010 congressional direction, NASA has initiated work toward a carbon monitoring system (CMS) that includes both maps of forest biomass and total carbon flux estimates. A goal of the project is to ensure that the products are useful to a wide community of scientists, managers, and policy makers, as well as to carbon cycle scientists. Understanding the needs and requirements of these data users is helpful not just to the NASA CMS program but also to the entire community working on carbon-related activities. To that end, this meeting brought together a small group of natural resource managers and policy makers who use information on forests in their work with NASA scientists who are working to create aboveground forest biomass maps. These maps, derived from combining remote sensing and ground plots, aim to be more accurate than current inventory approaches when applied at local and regional scales. Meeting participants agreed that users of biomass information will look to the CMS effort not only to provide basic data for carbon or biomass measurements but also to provide data to help serve a broad range of goals, such as forest watershed management for water quality, habitat management for biodiversity and ecosystem services, and potential use for developing payments for ecosystem service projects. Participants also reminded the CMS group that potential users include not only public sector agencies and nongovernmental organizations but also the private sector because much forest acreage in the United States is privately held and needs data for forest management. Additional key outcomes identified by meeting participants include the following: (1) Priority should be given to building into the biomass product ease of use and low costs (including costs of hardware, software, and analysis requirements), (2) CMS products should also be relevant to other biomass measures for forest watershed management, habitat protection for biodiversity, and assessment of markets for ecosystem services, (3) CMS leadership should engage with the Subsidiary Body for Scientific and Technological Advice of the United Nations Framework Convention on Climate Change as they establish measuring, reporting, and verification standards, and (4) CMS leadership should continue to keep sister agencies and other organizations informed as CMS develops, particularly via the agencies active in the U.S. Global Change Research Program Carbon Cycle Interagency Working Group (U.S. Geological Survey, U.S. Department of Agriculture, and National Oceanic and Atmospheric Administration) and nongovernmental organizations.

Forest↗

NASA NTRS1983

Snowpack ground-truth manual

As remote sensing increasingly becomes more of an operational tool in the field of snow management and snow hydrology, there is need for some degree of standardization of ""snowpack ground truth'' techniques. This manual provides a first step in standardizing these procedures and was prepared to meet the needs of remote sensing researchers in planning missions requiring ground truth as well as those providing the ground truth. Focus is on ground truth for remote sensors primarily operating in the microwave portion of the electromagnetic spectrum; nevertheless, the manual should be of value to other types of sensor programs. This first edition of ground truth procedures must be updated as new or modified techniques are developed.

Jones, E. B.↗

DOE OSTI2020

Smart Composite Pressure Vessels (SCPV) with Integrated Health Monitoring

The U.S. Department of Energy (DOE) is promoting and developing more energy efficient and environmentally friendly technologies that will enable America to use less petroleum. Hydrogen fuel cells – which directly convert the chemical energy in hydrogen to electricity with only water and heat as byproducts – are a very attractive solution that can enable this to happen. To date, DOE's efforts have culminated in commercial demonstration of on-board vehicular hydrogen storage systems that can allow for a driving range of greater than 300 miles. This requires storing 5 Kgs of hydrogen onboard a light vehicle. In order to store this quantity of hydrogen, the hydrogen gas needs to be stored in a composite overwrapped pressure vessel (COPV) at a very high internal pressure. The objective of the program was to demonstrate continuous and predictable health-monitoring of composite pressure vessels. A higher confidence in the operational safety of the vessels will lead to reduced burst factor of safety imposed by regulatory standards and hence will help reduce the structural wall thickness that drives the cost of the vessel. Highly optimized Type III (metal lined) and Type IV (polymer lined) COPVs that are manufactured using filament winding process have been designed and qualified for the above mentioned application. However, the main structural component of the COPVs is carbon fiber and the high cost of carbon fiber composite in a pressure vessel is a primary challenge in reducing the cost of gaseous hydrogen storage. Continuous and remote monitoring of structural health of the COPVs as well as optimization of the strength translation of carbon fibers have the potential to allow for reduced factor of safety, thereby reduced amount of carbon and associated cost of the vessel. In the current program, the project team including Steelhead Composites (SHC), University of Tennessee, Knoxville (UTK), Teijin Carbon America, Oak Ridge National Laboratory (ORNL) and LUNA designed, fabricated, and tested smart composite pressure vessels with integrated sensors. Iterative loops of design and testing using coupons, subscale STEB vessels and full size vessels proved that a new generation of high performance carbon fiber can be used for efficient design of Type 3 vessels for H2 storage. Novel analysis techniques were developed to predict the initiation and propagation of interlaminar damage inside the composite shell due to impact damage, a real threat in practical operation. Such an analysis scheme is typically not used in tank design but is an essential tool for health monitoring of composite vessels. Remote sensing of the key signatures of the tank’s operating parameters such as pressure, acceleration and humidity was demonstrated using a unique device that can wirelessly transmit and stream the data to a remote server. Fiber optic sensors were successfully integrated during fabrication of the tanks. These sensors provide a wealth of information regarding the structural health of the vessel when it is subsequently pressurized or subjected to impact damage. Excellent correlation was demonstrated between the fiber optic sensor and mechanical strain gage data, and between the measurements and analytical predictions.

08 HYDROGEN↗

NASA NTRSDate not supplied

In-Situ Detection of Process-Induced Porosity During Cure of Out-of-Autoclave Composites

Composite materials offer unique benefits in aerospace applications, including high strength-to-weight ratio, and are becoming increasingly used by industry manufacturers. Current manufacturing and processing methods can lead to defects in the composites, which are identified after fabrication using inspection methods. This study utilized a high-temperature ultrasonic inspection system to detect process-induced porosity in an out-of-autoclave (OOA) composite panel during cure. In order to perform ultrasonic scans in-situ during cure, the system needed to be able to operate at oven temperatures up to 200 °C. There are no commercially available ultrasonic scanning systems that can operate continuously at these temperatures, so an enclosure was fabricated to insulate the ultrasonic system in the curing oven. The enclosure housed a MISTRAS® motorized X-Y raster scanner and contact transducer (Olympus® X2002). The Olympus® X2002 contact transducer is a continuous high-temperature delay line transducer with a center frequency of 2.25 MHz. In order to prevent the inside of the enclosure from reaching high temperatures, a sparge pipe inside the cooling enclosure was connected to a liquid nitrogen (LN2) tank outside of the oven via insulated hoses. The cooling system was automatically controlled by a temperature controller that was programmed to open a solenoid valve along the hose at 31 ℃ and close at 28 ℃ inside the cooling enclosure. When the solenoid valve was open, LN2 would flow from the LN2 tank and vaporize prior to reaching cooling enclosure. A U-shaped sparge pipe had holes drilled along its length to uniformly introduce cold nitrogen gas into the cooling enclosure. This prevented the motors from ever reaching the maximum desired operating temperature of 38 ℃. In the bottom of the enclosure, the tool plate was placed with the composite facing the outside of the enclosure, exposing it to the temperatures of the oven. The tool plate was 63.5 mm thick borosilicate glass, which was chosen for its low ultrasonic attenuation and moderate thermal conductivity. A thin layer of ultrasonic couplant was placed on the tool plate. The transducer sent and received ultrasonic waves through the tool plate into the composite. A MISTRAS® Remote UT System performed all wave generation, analog to digital conversion, and data acquisition and processing. The transducer was connected directly to the Remote UT System via a high-temperature BNC cable (CD International, RG-316). Polyimide insulated copper wire was used to connect the scanner to a 2-axis motor drive, which was connected to the Remote UT System. The motor drive and Remote UT System were located outside the industrial oven. A diagram of the ultrasonic system is shown in Figure 1. Figure 1: Diagram of ultrasonic in-situ defect detection system. In this study, a porosity gradient was introduced into the carbon fiber reinforced polymer (CFRP) composite through a misfit of the part and caul plate. A 24-ply quasi-isotropic ([0/90, ±45]12S) composite panel was laid up using Newport® AS4C-M/NB321 out-of-autoclave (OOA) plain weave (PW) prepreg (42% resin content, 195 g/m2). The first 16 plies were 203 mm × 203 mm. Ply drops were incorporated into the panel by decreasing the length of plies 17-24. The sizes of each ply are included in Table 1. All plies were centered along their length (x-axis) creating a trapezoidal type cross-section. Table 1: Ply sizes Plies Length (mm) Width (mm) 1-16 203 203 17-18 102 203 19-20 85 203 21-22 68 203 23-24 51 203 A 15-5 stainless steel caul plate (Size: 203 × 203 × 1.2 mm) was placed on the laminate. The composite and caul plate were vacuum bagged to the tool plate. Per the product datasheet, Newport 321 can be cured between 121 °C and 149 °C, depending on service temperature, with a hold for 90-120 minutes. Based on prior thermal testing of the cooling enclosure, the desired composite temperature cycle could be attained when the air temperature of the oven was ramped to 160 °C at a rate of 1.7 °C/min with a 3 hour hold. The extended hold was not necessary to cure the composite, but did allow for additional scans at the cure temperature during preliminary testing. The composite panel was under vacuum pressure for the entire cure cycle. Under vacuum, the caul plate deformed causing high and low pressure regions. The low-pressure regions formed high porosity in the composite part. The ultrasonic data collected showed that the inspection system was able to monitor the evolution of porosity within the composite throughout the cure cycle. Fifty scans of a 203 mm × 51 mm (8 in. × 2 in.) area of the composite were completed throughout the cure cycle. The scan speed was set to 43 mm/s in the x-direction and 36 mm/s in the y-direction, with a 1.0 mm/pixel resolution in both directions. Each scan took approximately five minutes to complete. Figure 2 shows C-scan amplitude data (top view) from one scan during the cure cycle. The color map indicates the maximum amplitude (%) measured with a time gate that contains reflections from the back surface (furthest from the transducer in contact with the caul plate) of the composite. Because porosity in the composite increases the ultrasonic attenuation in the composite part, a higher amplitude (red) indicates low porosity and a lower amplitude (blue) indicates high porosity. The regions where the caul plate was applying increased pressure (center and ends of the panel) resulted in reduced porosity, whereas the ply drop regions had reduced pressure and thus had higher porosity. Figure 2: Amplitude C-scan (top view) of OOA composite from one scan during the 160 °C temperature hold. Higher amplitude (red) indicates low porosity. Lower amplitude (blue) indicates high porosity. A B-scan is a two-dimensional image plotting the ultrasonic signals from a single y-position at every x-location of the composite panel. The travel time (μs) of the ultrasonic wave (representing the through-thickness location) is plotted along the y-axis, and the ultrasonic wave signal is represented as a contour map. Based on the B-scan data, the location of the defects with respect to the composite thickness was able to be determined. The ply drop regions had high porosity near the front (tool plate) surface of the composite (Figure 3). Figure 3: B-scan (cross-section view) of OOA composite from one scan during the 160 °C temperature hold. Using the data obtained from amplitude C-scans and B-scans throughout the cure cycle, the high and low porosity regions within the composite laminate were detected and localized with high spatial resolution. This paper will discuss the evolution of porosity content in the OOA composite during cure. OOA tests aided the transition of this system to an autoclave, which is the primary method of curing aerospace-grade thermoset composites.

Tyler B. Hudson↗

NASA NTRS2018

NASA’s Mid-Atlantic Communities and Areas at Intensive Risk Demonstration: Translating Compounding Hazards to Societal Risk

Remote sensing provides a unique perspective on our dynamic planet, tracking changes and revealing the course of complex interactions. Long term monitoring and targeted observation combine with modeling and mapping to provide increased awareness of hydro-meteorological and geological hazards. Disasters often follow hazards and the goal of NASA’s Disasters Program is to look at the earth as a highly coupled system to reduce risk and enable resilience. Remote sensing and geospatial science are used as tools to help answer critical questions that inform decisions. Data is not the same as information, nor does understanding of processes necessarily translate into decision support for disaster preparedness, response and recovery. Accordingly, NASA is engaging the scientific and decision-support communities to apply remote sensing, modeling, and related applications in Communities and Areas at Intensive Risk (CAIR). In 2017, NASA’s Applied Sciences Disasters Program hosted a regional workshop to explore these issues with particular focus on coastal Virginia and North Carolina. The workshop brought together partners in academia, emergency management, and scientists from NASA and partnering federal agencies to explore capabilities among the team that could improve understanding of the physical processes related to these hazards, their potential impact to changing communities, and to identify methodologies for supporting emergency response and risk mitigation. The resulting initiative, the mid-Atlantic CAIR project, demonstrates the ability to integrate satellite derived earth observations and physical models into actionable, trusted knowledge. Severe storms and associated storm surge, sea level rise, and land subsidence coupled with increasing populations and densely populated, aging critical infrastructure often leave coastal regions and their communities extremely vulnerable. The integration of observations and models allow for a comprehensive understanding of the compounding risk experienced in coastal regions and enables individuals in all positions make risk-informed decisions. This initiative uses a representative storm surge case as a baseline to produce flood inundation maps. These maps predict building level impacts at current day and for sea level rise (SLR) and subsidence scenarios of the future in order to inform critical decisions at both the tactical and strategic levels. To accomplish this analysis, the mid-Atlantic CAIR project brings together Federal research activities with academia to examine coastal hazards in multiple ways: 1) reanalysis of impacts from 2011 Hurricane Irene, using numerical weather modeling in combination with coastal surge and hydrodynamic, urban inundation modeling to evaluate combined impact scenarios considering SLR and subsidence, 2) remote sensing of flood extent from available optical imagery, 3) adding value to remotely sensed flood maps through depth predictions, and 4) examining coastal subsidence as measured through time-series analysis of synthetic aperture radar observations. Efforts and results are published via ArcGIS story maps to communicate neighborhoods and infrastructure most vulnerable to changing conditions. Story map features enable time-aware flood mapping using hydrodynamic models, photographic comparison of flooding following Hurricane Irene, as well as visualization of heightened risk in the future due to SLR and land subsidence.

Rogers, Laura↗

NASA NTRS1973

Earth observations from space: Outlook for the geological sciences

Remote sensing from space platforms is discussed as another tool available to geologists. The results of Nimbus observations, the ERTS program, and Skylab EREP are reviewed, and a multidisciplinary approach is recommended for meeting the challenges of remote sensing.

Short, N. M.↗

DOE OSTI2023

A Cybersecurity Testbed for Smart Buildings

Smart buildings are equipped with a plethora of cyber-physical systems, such as Internet of Things (IoT) devices and building automation systems. These devices, especially in commercial buildings, use legacy communications and hardware that were not designed with cybersecurity in mind. With increasing cyber threats in recent years, smart buildings have become an increasing target for attacks, but not enough published data are available from these incidents to study or replicate the scenarios to defend buildings. As part of the U.S. Department of Energy-funded project focusing on developing the Building Intelligence with Layered Defense Using Security-Constrained Optimization and Security Risk Detection (BUILD-SOS) platform, we developed a cybersecurity test bed for smart buildings. This test bed includes a building simulation tool, virtual devices, emulated operational technology networks, and remote hardware-in-the-loop. Using this test bed, we performed different cyberattacks on the smart building model and collected both physical building data, to understand the impacts on the building, and network data, to aid in separating mechanical faults from cyberattacks during the detection. This test bed is a significant tool in protecting smart buildings from cyberattacks because it can aid in both cybersecurity analysis and the evaluation of other cyberattack detection tools by testing the tools in a secure environment without impacting the building operations.

cyber-physical systems↗

DOE OSTI2024

A Cybersecurity Testbed for Smart Buildings

Smart buildings are equipped with a plethora of cyber-physical systems, such as Internet of Things (IoT) devices and building automation systems. These devices, especially in commercial buildings, use legacy communications and hardware that were not designed with cybersecurity in mind. With increasing cyber threats in recent years, smart buildings have become an increasing target for attacks, but not enough published data are available from these incidents to study or replicate the scenarios to defend buildings. As part of the U.S. Department of Energy-funded project focusing on developing the Building Intelligence with Layered Defense Using Security-Constrained Optimization and Security Risk Detection (BUILD-SOS) platform, we developed a cybersecurity test bed for smart buildings. This test bed includes a building simulation tool, virtual devices, emulated operational technology networks, and remote hardware-in-the-loop. Using this test bed, we performed different cyberattacks on the smart building model and collected both physical building data, to understand the impacts on the building, and network data, to aid in separating mechanical faults from cyberattacks during the detection. This test bed is a significant tool in protecting smart buildings from cyberattacks because they can aid in both cybersecurity analysis and the evaluation of cyberattack detection tools by testing the tools in a secure environment without impacting the building operations.

alfalfa↗

NASA NTRS1967

Report 2: First Application of the Successive Transformation Method

Report 1 of these studies described a basic method for predicting lunar surface temperatures, using readings recorded by Surveyor I and extrapolating to obtain surface temperatures in other selected areas. The areas selected were those considered as potential Apollo landing sites. This second report indicates that the temperature isotherms are directly related to the topographical profile of the surface areas they cover. If, after further observations by Surveyor 11, it becomes evident that the "Successive Transformation Method" provides accurate temperature data, this technique would become a valuable tool for charting the profile of any remote surface where manned spacecraft could be landed.

Rojas, Hector R.↗

NASA NTRS1978

Future data processing and its effect on spaceborne sensors

Remotely sensed data are attaining a new stature. New model for their use are being developed. Data delays are being overcome, and consideration is being given to multiple satellites and platforms providing shorter-interval repeat coverage. Statewide data systems are being developed to take advantage of remotely sensed data as a new analysis tool.

Billingsley, F. C.↗

NASA NTRS1979

LANDSAT's role in state coastal management programs

The framework for state programs found in the Coastal Zone Management Act and examples of state opportunities to use LANDSAT are presented. Present activities suggest that LANDSAT remote sensing can be an efficient, effective tool for land use planning and coastal zone management.

Source record↗

NASA NTRS1982

Computational modeling for the study of multispectral sensor systems and concepts

A computational model of the deterministic and stochastic processes involved in remote sensing is being developed as a tool for studying multispectral sensor systems and concepts. The goal is to improve the efficiency of sensor systems for routine worldwide monitoring of earth resources and the environment. Preliminary computational results are presented for simple models of the natural variability of atmospheric radiative transfer and surface reflectance. These results illustrate the dependence of classification accuracy on the selection of sensor spectral channels and data processing algorithms.

Huck, F. O.↗

NASA NTRS1994

A technique for determining cloud free versus cloud contaminated pixels in satellite imagery

Weather forecasting has been called the second oldest profession. To do so accurately and with some consistency requires an ability to understand the processes which create the clouds, drive the winds, and produce the ever changing atmospheric conditions. Measurement of basic parameters such as temperature, water vapor content, pressure, windspeed and wind direction throughout the three dimensional atmosphere form the foundation upon which a modern forecast is created. Doppler radar, and space borne remote sensing have provided forecasters the new tools with which to ply their trade.

Wohlman, Richard A.↗

NASA NTRS2000

The Sandmeier Field Goniometer: A Measurement Tool for Bi-Directional Reflectance

Recent activities at the Remote Sensing Program at Stennis Space Center have identified the need to properly verify and validate data provided by the remote sensing community. One important variable, which effects remote sensing data is bi-directional reflectance distribution (BRDF). In order to quantify the effects of BRDF on man-made and natural ground targets, the Stennis Verification & Validation (V&V) team commissioned the Systems Engineering Division at NASA Ames Research Center to develop a Field Goniometer for use at the V&V Large Target Range and for various ground truthing missions. The Swiss Field Goniometer (FIGOS) was used as a benchmark instrument to design the new state of the art Sandmeier Field Goniometer (SGF), named after Stefan Sandmeier, developer of FIGOS. After establishing requirements for the SFG, design efforts began in early May 1998. The design of the SFG was completed in September 1998. Manufacturing, construction, and testing was completed in May 1999. The SFG was shipped to NASA SSC and fully operational by June 1999.

Turner, Mark↗

NASA NTRS2011

Use of Cold Radiometers in Several Thermal/Vacuum Tests

We have developed a low cost low temperature broadband radiometer for use with low temperature tests as a diagnostic tool for measuring stray thermal radiation and remote measurement of material properties. So far these radiometers have been used in two large thermal/vacuum tests for the James Webb Space Telescope (JWST) Project. In the first test the radiometers measured stray radiation in a test of part of the JWST sunshield, and in the second test the radiometers were used to measure the reflectivity and specularity of black Z307 painted aluminum walls on a 25 K cooled shroud. These results will be presented as well as plans for future tests to measure the residual energy through a baffled aperture in the shroud and other stray thermal energy measurements.

DiPirro, M.↗