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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Preliminary Study of JPSS-1/NOAA-20 VIIRS Day-Night Band Straylight Characterization and Correction Methods

The JPSS-1 (now named NOAA-20) VIIRS instrument has successfully operated since its launch in November 18, 2017. A panchromatic channel onboard NOAA-20 VIIRS is called the day-night band (DNB). With its large dynamic range and high sensitivity, the DNB detectors can make observations during both daytime and nighttime. However, the DNB night image quality is affected by the straylight contamination. In this study, we focused on Earth view data in the midto-high latitude of the northern and southern hemispheres when spacecraft is crossing the day/night terminators at the beginning of NOAA-20 mission. Based on on-orbit data analysis from previous VIIRS sensor onboard S-NPP mission, straylight contamination mainly depends on the Earth-Sun-spacecraft geometry, and it is also detector and scan-angle dependent. Inter-comparison investigation of straylight behavior in both SNPP and NOAA-20 instruments will be conducted to better understand straylight characteristics. The preliminary study has been performed in this paper to mitigate straylight contamination for NOAA-20VIIRS DNB night images. The effectiveness of the straylight correction algorithm, directly adapted from the S-NPP DNB, is assessed for night images in the day/night terminators. Further work has been identified to improve current straylight correction methodology and DNB-based environmental data products.NOAA-20.

Day-Night Band↗
NASA NTRS2018

On-Orbit Special Testing of NOAA-20/JPSS-1 ATMS

The second Advanced Technology Microwave Sounder (ATMS) recently launched November 2017 on the Joint Polar Satellite System-l satellite (JPSS-l), now re-named NOAA-20. It joins the first ATMS flight unit aboard the Suomi NPP (S-NPP) satellite, as well as older sounders-the Advanced Microwave Sounding Units A & B (AMSU-A/B) and Microwave Humidity Sounder (MHS)-on polar-orbiting operational weather satellites. Together, these sounders provide critical all-weather temperature and humidity profile information for Numerical Weather Prediction (NWP) models. This paper presents results from a number of special post-launch tests used to characterize the instrument and provide unique calibration information. These special tests-long stares, alternate techniques for lunar intrusion mitigation and geolocation, spacecraft maneuvers, special scan modes, comparisons with NWP models-require non-standard modes of operation or data analysis, and can only be conducted during commissioning, prior to the start of regular forecast observations.

Kim, Edward↗
NASA NTRS2019

NOAA-20 ATMS Status: ATMS SDR Team

Data quality looks better than Suomi-NPP (Suomi National Polar-orbiting Partnership): similar biases. Smaller standard deviation of first guess departures and diagnosed observation errors. Weaker striping signal than Suomi-NPP ATMS (Advanced Technology Microwave Sounder). Improved first guess fits to: temperature observations (AMSU-A (Advanced Microwave Sounding Unit-A), CrIS (Cross-track Infrared Sounder), GPSRO (Global Positioning System Radio Occultation)); Humidity observations (MHS (Microwave Humidity Sounder), GEO CSRs (Geostationary Orbit Clear Sky Radiances)). Indicates improved accuracy of short range temperature and humidity forecasts. Neutral to slightly positive forecast scores.

Sensor Data Record (SDR)↗
NASA NTRS2019

TPSAS-NF1676L-32323-DND

The GSICS VIS/NIR subgroup has several items to discuss and to provide a brief summary of the GSICS VIS/NIR activities. The first item is currently using Aqua-MODIS as the visible calibration reference. The plan is to migrate to NPP-VIIRS as the visible calibration reference. Then official source is the NOAA NPP VIIRS dataset, which is only archived with V0. However, NOAA has updated the calibration known as V2. The specifics will be discussed of how to scale the V0 visible radiances to the V2 standard. Second item is to outline a deep convective cloud (DCC) paper visible calibration paper with input from the various agencies using the GSICS DCC calibration approach. Also, to finalize the solar spectra selection. Lastly, to start the conversation with Rayleigh scattering calibration. Several slides will be compile using conclusions from GSICS web meetings, which are compiled from input across multiple agencies. Topics include improvements in spectral band adjustment factors, desert calibration, and homogenization of data records.

David Doelling↗
NASA NTRSDate not supplied

TPSAS-NF1676L-27483-DND

scene to retrieve their microphysical properties. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the infrared channels (6.72 Âμm, 7.33 Âμm, 13.3 Âμm,13.6 Âμm, 13.9 Âμm, and 14.2 Âμm) available on the Terra and Aqua Moderate Resolution Imaging Spectroradiometers (MODIS) to build its algorithms to retrieval cloud properties. Unfortunately, The Visible Infrared Imaging Radiometer Suite (VIIRS) on board Suomi-NPP (National Polar-Orbiting Partnership) lacks these particular measurements. While conducting research using VIIRS data, it is desirable to bring these data into the VIIRS resolution. The Cross-track Infrared Sounder (CrIS), which is also on board Suomi-NPP, has these infrared channels. This paper describes a method to map the CrIS spectral radiances of CO2 and water vapor to VIIRS, with the mapping software in ATOVS and AVHRR Pre-processing (AAPP) package provided by Satellite Application Facilities for Numerical Weather Prediction (NWP SAF). This method is validated comparing mapped10.763 Âμm from CrIS with M15 from VIIRS. The mapped CO2 and water vapor channels were then created and combined with the conventional VIIRS product, as well as compared against corresponding channels of Aqua MODIS instrument.

Yan Chen↗
NASA NTRS2020

Uncertainties in CERES Top-of-Atmosphere Fluxes Caused by Changes in Accompanying Imager

The Clouds and the Earth’s Radiant Energy System (CERES) project provides observations of Earth’s radiation budget using measurements from CERES instruments on board the Terra, Aqua, Suomi National Polar-orbiting Partnership (S-NPP), and NOAA-20 satellites. The CERES top-of-atmosphere (TOA) fluxes are produced by converting radiance measurements using empirical angular distribution models, which are functions of cloud properties that are retrieved from imagers flying with the CERES instruments. As the objective is to create a long-term climate data record, not only calibration consistency of the six CERES instruments needs to be maintained for the entire time period, it is also important to maintain the consistency of other input data sets used to produce this climate data record. In this paper, we address aspects that could potentially affect the CERES TOA flux data quality. Discontinuities in imager calibration can affect cloud retrieval which can lead to erroneous flux trends. When imposing an artificial 0.6 per decade decreasing trend to cloud optical depth, which is similar to the trend difference between CERES Edition 2 and Edition 4 cloud retrievals, the decadal SW flux trend changed from −0.3 5 ± 0.18 Wm −2 to 0.61 ± 0.18 Wm −2 . This indicates that a 13% change in cloud optical depth results in about 1% change in the SW flux. Furthermore, different CERES instruments provide valid fluxes at different viewing zenith angle ranges, and including fluxes derived at the most oblique angels unique to S-NPP (>66 ∘ ) can lead to differences of 0.8 Wm −2 and 0.3 Wm −2 in global monthly mean instantaneous SW flux and LW flux. To ensure continuity, the viewing zenith angle ranges common to all CERES instruments (<66 ∘ ) are used to produce the long-term Earth’s radiation budget climate data record. The consistency of cloud properties retrieved from different imagers also needs to be maintained to ensure the TOA flux consistency.

Wenying Su↗
NASA NTRS2020

Comparison of the MODIS and VIIRS Thermal Emissive Band Radiometric Calibration

Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) are major instruments for Earth science observations.Nearly 40 MODIS scientific products and a wide range of VIIRS environmental data records are produced using their global observations. The consistency of the MODIS and VIIRS calibrated data is important for the study of Earth science. This article assesses the calibration consistency of the Aqua MODIS and VIIRS thermal emissive band (TEB) data. To remove the impact of the mismatched relative spectral response (RSR) on the comparisons, the simultaneous nadir observation data from the cross-track infrared sounder (CrIS) and the infrared atmospheric sounding interferometer (IASI) are used as references in two different methods to independently verify the consistency. The comparisons of the MODIS and VIIRS TEB calibrated data show that the brightness temperature (BT) differences for comparable bands between MODIS and VIIRS are in general within 0.2 K for BT larger than 230 K. The differences of all comparable MODIS and VIIRS TEBs are consistent over time. MODIS measurements agree better with N20 VIIRS than with Suomi National Polar-orbiting Partnership (S-NPP) VIIRS. The S-NPP VIIRS measurements are higher than N20 VIIRS, within 0.1 Kfor long-wave infrared (LWIR) bands and 0.3 K for band M13.

Calibration↗
NASA NTRS2018

Larch (Larix dahurica Turcz) growth response to climate change in the Siberian permafrost zone

Larch-dominant communities are the most extensive high-latitude forests in Eurasia and are experiencing the strongest impacts from warming temperatures. We analyzed larch (Larix dahurica Turcz) growth index (GI) response to climate change. The studied larch-dominant communities are located within the permafrost zone of Northern Siberia at the northern tree limit (ca. N 67° 38′, E 99° 07′). Methods included dendrochronology, analysis of climate variables, root zone moisture content, and satellitederived gross (GPP) and net (NPP) primary productivity. It was found that larch response to warming included a period of increased annual growth increment (GI) (from the 1970s to ca. 1995) with a follow on GI decline. Increase in GI correlated with summer air temperature, whereas an observed decrease in GI was caused by water stress (vapor pressure deficit and drought increase). Water stress impact on larch growth in permafrost was not observed before the onset of warming (ca. 1970). Water limitation was also indicated by GI dependence on soil moisture stored during the previous year. Water stress was especially pronounced for stands growing on rocky soils with low water-holding capacity. GPP of larch communities showed an increasing trend, whereas NPP stagnated. A similar pattern of GI response to climate warming has also been observed for Larix sibirica Ledeb, Pinus sibirica Du Tour, and Abies sibirica Ledeb in the forests of southern Siberia. Thus, warming in northern Siberia permafrost zone resulted in an initial increase in larch growth from the 1970s to the mid-1990s. After that time, larch growth increment has decreased. Since ca. 1990, water stress at the beginning of the vegetative period became, along with air temperature, a main factor affecting larch growth within the permafrost zone.

Larix dahurica↗
NASA NTRS2021

Ecosystem age-class dynamics and distribution in the LPJ-wsl v2.0 global ecosystem model

Forest ecosystem processes follow classic responses with age, peaking production around canopy closure and declining thereafter. Although age dynamics might be more dominant in certain regions over others, demographic effects on net primary production (NPP) and heterotrophic respiration (Rh) are bound to exist. Yet, explicit representation of ecosystem demography is notably absent in many global ecosystem models. This is concerning because the global community relies on these models to regularly update our collective understanding of the global carbon cycle. This paper aims to present the technical developments of a computationally efficient approach for representing age-class dynamics within a global ecosystem model, the Lund–Potsdam–Jena – Wald, Schnee, Landschaft version 2.0 (LPJ-wsl v2.0) dynamic global vegetation model and to determine if explicit representation of demography influenced ecosystem stocks and fluxes at global scales or at the level of a grid cell. The modeled age classes are initially created by simulated fire and prescribed wood harvesting or abandonment of managed land, otherwise aging naturally until an additional disturbance is simulated or prescribed. In this paper, we show that the age module can capture classic demographic patterns in stem density and tree height compared to inventory data, and that simulated patterns of ecosystem function follow classic responses with age. We also present two scientific applications of the model to assess the modeled age-class distribution over time and to determine the demographic effect on ecosystem fluxes relative to climate. Simulations show that, between 1860 and 2016, zonal age distribution on Earth was driven predominately by fire, causing a 45- to 60-year difference in ages between older boreal (50–90° N) and younger tropical (23° S–23° N) ecosystems. Between simulation years 1860 and 2016, land-use change and land management were responsible for a decrease in zonal age by −6 years in boreal and by −21 years in both temperate (23–50° N) and tropical latitudes, with the anthropogenic effect on zonal age distribution increasing over time. A statistical model helped to reduce LPJ-wsl v2.0 complexity by predicting per-grid-cell annual NPP and Rh fluxes by three terms: precipitation, temperature, and age class; at global scales, R2 was between 0.95 and 0.98. As determined by the statistical model, the demographic effect on ecosystem function was often less than 0.10 kg C/sq. myr but as high as 0.60 kg C/sq. myr where the effect was greatest. In the eastern forests of North America, the simulated demographic effect was of similar magnitude, or greater than, the effects of climate; simulated demographic effects were similarly important in large regions of every vegetated continent. Simulated spatial datasets are provided for global ecosystem ages and the estimated coefficients for effects of precipitation, temperature and demography on ecosystem function. The discussion focuses on our finding of an increasing role of demography in the global carbon cycle, the effect of demography on relaxation times (resilience) following a disturbance event and its implications at global scales, and a finding of a 40 Pg C increase in biomass turnover when including age dynamics at global scales. Whereas time is the only mechanism that increases ecosystem age, any additional disturbance not explicitly modeled will decrease age. The LPJ-wsl v2.0 age module represents another step forward towards understanding the role of demography in global ecosystems.

LPJ-wsl↗
NASA NTRS2021

Assessment of VIIRS Day-Night Band High Gain Calibration Using Stars

The VIIRS has a unique spectral band that can sense reflected light from space during both day and nighttime, thus referred to as the day-night band (DNB). This band operates in three different gain stages: low, mid, and high gain (LG, MG, and HG) that cover a remarkable dynamic range with its HG stage being extremely sensitive to low-light scenes. Similar to its reflective solar bands, the VIIRS uses an on-board solar diffuser for its DNB LG stage calibration, whereas the DNB MG and HG calibrations are performed using relative or ratioing approaches. In this paper, we provide an assessment of VIIRS DNB HG calibrations using stars that appear in the field-of-view of its space view (SV), focusing on the computation of the gain trending and associated tool development. We also describe various strategies and procedures developed for DNB HG calibration stability monitoring and inter-comparisons among different VIIRS instruments and discuss some of the complications and limits to this approach, including under-sampling of the stellar image, saturation, and crowding. For S-NPP VIIRS, it includes the use of the modulated relative spectral response (RSR) resulting from wavelength-dependent degradation of the sensor optics. Results show that the star-based response trending for the DNB HG is consistent with that derived from on-board solar diffuser and that the calibration difference between S-NPP and N-20 VIIRS DNB requires additional effort to address, especially for research studies and applications using data from both sensors.

VIIRS↗
NASA NTRS2020

Monitoring VIIRS Thermal Emissive Bands Long-Term Performance Using Lunar Observations

Two Visible Infrared Imaging Radiometer Suite (VIIRS) instruments are currently operating in space, one onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite launched on October 28, 2011 and the other onboard the NOAA-20 satellite launched on November 18, 2017. The performance of the seven VIIRS thermal emissive bands (TEBs) is monitored via on-orbit calibration data, the analysis of Earth view observations, as well as inter-comparisons with other sensors. The Moon has been used as a unique invariant target for on-orbit sensor calibration because its surface property is considered extremely stable over time in spectra, radiometry, and geometry with a repeatable lunar phase. This paper presents the assessments of the S-NPP and NOAA-20 VIIRS TEB on-orbit calibration stability using near-monthly scheduled lunar observations over their respective missions. The methodology previously developed for MODIS is now applied to VIIRS to monitor the TEB long-term stability by extracting and trending the lunar brightness temperatures from selected unsaturated pixels. It includes a correction applied to reduce any impact from the Sun–Moon geometry (e.g. Sun-Moon distance variation). The results show that the mission-long brightness temperature trends from the lunar surface are stable for all VIIRS TEBs, despite noticeable seasonal variations in the lunar thermal emissive radiance.

VIIRS↗
NASA NTRS2022

Estimates of Diurnal and Daily Net Primary Productivity Using the Geostationary Ocean Color Imager (GOCI) Data

For the past three decades, polar-orbiting ocean color satellites have provided local, regional to global scale estimates of oceanic net primary production that have greatly aided studies of ocean carbon cycling, food web dynamics and climate change. Despite considerable progress, accurate estimates of daily ocean productivity from space have not been realized because polar-orbiting satellites are unable to account for variations in phytoplankton physiology and carbon fixation rates from changing incident irradiance levels over the course of the day. Here we have attempted to exploit the unique short-temporal measurements provided by the Korean Geostationary Ocean Color Imager (GOCI), to obtain for the first time, diurnal and daily measurements of surface- and euphotic-column integrated Net Primary Productivity (NPP). These estimates are based on the Absorption Based Productivity Model (AbPM), and are calibrated with a bio-optical database of measurements made at different times of the day during the Korea-US Ocean Color (KORUS-OC) cruise in May–June 2016. Photo-physiological rate estimates, varied across different water types encountered around the Korean Peninsula, but on account of their limited number, were regionally scaled through the use of dynamic optical-biogeochemical (O-BGC) Biomes. Comparisons of GOCI derived estimates of daily and weekly integrated NPP against in-situ measurements, clearly underscore the superiority of geostationary over polar-orbiting ocean color satellites, which consider the strong short-term fluctuations in phytoplankton light absorption and incident irradiance fields over the course of the day.

Diurnal productivity↗
NASA NTRS2023

Assessment of the Impact of Discontinuity in Satellite Instruments and Retrievals on Global PM2.5

Exposure to fine particulate matter (PM2.5) is the leading environmental risk factor for mortality globally. Satellite-derived estimates of surface PM2.5 developed from a combination of satellites, simulations, and ground monitor data are relied upon for health impact studies. The ability to develop satellite-derived PM2.5 estimates requires the continued availability of aerosol optical depth (AOD) sources. This work examines the impact of the addition or loss of satellite AOD data sources on global PM2.5 estimation and the impact of continuing the longterm record with AOD from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi-National Polar orbiting Partnership (S-NPP) satellite after the loss of the MODIS (MODerate resolution Imaging Spectroradiometer) and MISR (Multi-angle Imaging Spectroradiometer) instruments on board the Terra and Aqua satellites. We find that the addition of VIIRS S-NPP AOD products to geophysical PM2.5 estimates from satellites and simulations causes regional differences that correspond to differences in the VIIRS and MODIS Deep Blue AOD algorithms and sampling. Changes in long-term trends and timeseries due to the addition or loss of AOD data sources are generally within their uncertainties. Statistical fusion with ground monitor data partially corrects for changes due to sampling differences when introducing the VIIRS AOD products, but uncertainty remains over desert regions where ground monitor coverage is sparse. This work provides promise for the sustained development of global satellite-derived PM2.5 estimates, despite discontinuities in instruments and retrieval methods.

Remote sensing↗
NASA NTRSDate not supplied

Understanding Plant Nitrogen Form Preference Responses to Elevated CO2 Earth and Space Environments

Future long-duration missions to the International Space Station (ISS) and beyond will require a sustainable supply of food to support human crews. The spaceflight cabin environment often contains very high concentrations of CO2, and it is therefore crucial to understand plant responses to elevated CO2 (eCO2) environments. Much focus has been given to plant photosynthetic and performance parameters in response to eCO2, but studies on the effects of eCO2 on nitrogen uptake are poorly understood. Our previous work at The University of Sheffield, UK using novel stable isotope approaches has shown enhanced ammonium uptake and preference compared to nitrate at eCO2 in varieties of spring barley, hypothesized to be an indirect consequence of changes in photosynthesis and photorespiration. However, several varieties did not display altered preference under eCO2 and the universality of this response remains to be understood. In this NASA NPP project, several candidate crop species such as lettuce, radish and tomato will be screened using stable isotopes to assess whether N preference changes in favor of ammonium in response to eCO2 and whether this remains true at super-elevated CO2 (seCO2), which is often experienced on the ISS. Photosynthetic and related measurements will help to disentangle the relationship between these responses and photosynthesis. This work will enable the development of optimized nutrient regimes for candidate crops in space and in future Lunar and Martian habitats and will pave the way for selection of crop varieties adapted to an eCO2 and/or seCO2 environment. Moreover, this research will further our understanding of plant responses to the eCO2 environment brought about by climate change, allowing the development of future-proof crops that will help to maintain food security. This NPP Fellowship is funded by NASA Space Biology.

Luke Leslie Fountain↗
NASA NTRSDate not supplied

Understanding Plant Nitrogen Form Preference Responses to Elevated CO2 Earth and Spaceflight Cabin Environments

Future long-duration missions to the International Space Station (ISS) and beyond will require a sustainable supply of food to support human crews. The spaceflight cabin environment often contains very high concentrations of CO2, and it is therefore crucial to understand plant responses to elevated CO2 (eCO2) environments. Much focus has been given to plant photosynthetic and performance parameters in response to eCO2, but studies on the effects of eCO2 on nitrogen uptake are poorly understood. Our previous work at The University of Sheffield, UK using novel stable isotope approaches has shown enhanced ammonium uptake and preference compared to nitrate at eCO2 in varieties of spring barley, hypothesised to be an indirect consequence of changes in photosynthesis and photorespiration. However, several varieties did not display altered preference under eCO2 and the universality of this response remains to be understood. In this NASA NPP project, several candidate crop species such as lettuce, radish and tomato will be screened using stable isotopes to assess whether N preference changes in favor of ammonium in response to eCO2 and whether this remains true at super-elevated CO2 (seCO2), which is often experienced on the ISS. Photosynthetic and related measurements will help to disentangle the relationship between these responses and photosynthesis. This work will enable the development of optimized nutrient regimes for candidate crops in space and in future Lunar and Martian habitats and will pave the way for selection of crop varieties adapted to an eCO2 and/or seCO2 environment. Moreover, this research will further our understanding of plant responses to the eCO2 environment brought about by climate change, allowing the development of future-proof crops that will help to maintain food security. This NPP Fellowship is funded by NASA Space Biology.

Luke Fountain↗
NASA NTRSDate not supplied

Understanding Plant Nitrogen Form Preference Responses to Elevated CO2 Earth and Spaceflight Cabin Environments.

Future long-duration missions to the International Space Station (ISS) and beyond will require a sustainable supply of food to support human crews. The spaceflight cabin environment often contains very high concentrations of CO2, and it is therefore crucial to understand plant responses to elevated CO2 (eCO2) environments. Much focus has been given to plant photosynthetic and performance parameters in response to eCO2, but studies on the effects of eCO2 on nitrogen uptake are poorly understood. Our previous work at The University of Sheffield, UK using novel stable isotope approaches has shown enhanced ammonium uptake and preference compared to nitrate at eCO2 in varieties of spring barley, hypothesised to be an indirect consequence of changes in photosynthesis and photorespiration. However, several varieties did not display altered preference under eCO2 and the universality of this response remains to be understood. In this NASA NPP project, several candidate crop species such as lettuce, radish and tomato will be screened using stable isotopes to assess whether N preference changes in favor of ammonium in response to eCO2 and whether this remains true at super-elevated CO2 (seCO2), which is often experienced on the ISS. Photosynthetic and related measurements will help to disentangle the relationship between these responses and photosynthesis. This work will enable the development of optimized nutrient regimes for candidate crops in space and in future Lunar and Martian habitats and will pave the way for selection of crop varieties adapted to an eCO2 and/or seCO2 environment. Moreover, this research will further our understanding of plant responses to the eCO2 environment brought about by climate change, allowing the development of future-proof crops that will help to maintain food security. This NPP Fellowship is funded by NASA Space Biology.

space plant biology↗
DOE OSTI2020

Stochastic Analysis for Long Term Capital Structures, Systems, and Components Refurbishment and Replacement

As commercial Nuclear Power Plants (NPPs) pursue extended plant operation in the form of Second License Renewal (SLR), opportunities exist for these plants to provide capital investments to ensure long-term safe and economic performance. At the current time, several utilities have announced an intention to pursue extended operation for one or more of their NPPs via SLR . The goal of this research is to develop a risk-informed approach to evaluate and prioritize plant capital investments made in preparation for, and during the period of, extended plant operations to support decisions for NPP operations. Since the capital investments are influenced by various factors, such as markets, safety and regulatory, the decision-making process of NPP operations should take into account relevant factors for balancing risks, costs and profits. The traditional method of capital budgeting is based on the priority list of candidate projects using economic measures such as benefit-investment ratio, net present value (NPV) and internal rate of return. In the literatures, the problem of capital budgeting or the variant can be represented by an appropriate knapsack problem. The knapsack approach to capital budgeting takes as input as investment, along with the cost and profit of each project. The objective of capital budgeting is to find the combination of the binary decisions for every investment such that the overall profit is as large as possible. The output is a collection of projects to be carried out, and we refer this selected collection of projects as a project portfolio. One limitation of traditional optimization models for capital budgeting is that they do not account for risk/uncertainty in profit and cost streams associated with individual projects, they do not account for risk in resource availability in future years [1,2,3]. Projects can incur cost over-runs, especially when projects are large, performed infrequently, and when there is risk regarding technical viability, external contractors, and/or suppliers of requisite parts and materials. Occasionally, projects are performed ahead of schedule and with cost savings. Planned budgets for capital improvements can be cut and key personnel may be lost. Or, there may be surprise windfalls in budgets for maintenance activities due to decreased costs for “unplanned” maintenance. In these cases, how should we resolve capital budgeting when we have risk forecasts for costs, profits and budgets? One approach we proposed in this summary is to re-solve the optimization models based on assumed statistical distributions of given parameters. If these distributions were not available, a two-stage stochastic optimization approach can be used to provide priority lists to decision-makers to support better risk-informed decisions [4, 5]. In this summary, we will only focus on the first approach.

42 ENGINEERING↗
DOE OSTI2021

Using Qualified On-Site Nuclear Power Plant Simulators in Human Factors Validations of Control Room Upgrades

Existing commercial nuclear power plants (NPPs) are valuable assets in the infrastructure portfolio of the United States (U.S.) because they safely and reliably generate about 1/5th of all the electricity used. The instrumentation and control (I&C) systems in commercial NPPs are the ‘eyes and ears' of the operator, allowing operators to maintain situation awareness, thereby allowing the plant to operate safely and efficiently for all phases of operation. Because the I&C systems in NPPs are still mostly based on analog technologies, which are reliable but not especially cost-effective, upgrading the existing I&C in com-mercial NPPs to new digital I&C is very important. Furthermore, simulators and simulation are critical human factors engineering tools for this I&C modernization work. NPP control room simulators are essential test beds to simulate normal, abnormal, and emergency operations that allow human factors researchers to safely and realistically evaluate early design phase prototypes of the upgraded digital I&C, and validate final as-built digital I&C systems that have been modernized deployed in NPPs. This paper describes research performed using qualified on-site NPP simulators to perform human factors validations of digital I&C control room upgrades.

99 GENERAL AND MISCELLANEOUS↗