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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Creation of Synthetic Electric Grids (SPP/MISO) Supporting PERFORM (Final Report)

Over the course of the project, two “realistic but not real” synthetic transmission-level grid models over the SPP-MISO and ERCOT footprints were created to provide more realistic data and increase the reliability and resiliency of the grids under a variety of scenarios. The synthetic ERCOT transmission grid is compatible with the distribution grid developed in collaboration with NREL. All generators are based on the EIA 860 data and a column with EIA plant code and Gen ID is added to generators of both grids so that they can be easily mapped. The improvements are also made to electric grids including N-1 contingencies with some remedial actions, improving the transmission lines to avoid lines in lakes, including an HVDC line to the SPP-MISO case, providing several generator parameters and their temporal constraints that were not included in EIA 860 form, generators’ cost curves, load offer curves, adding phase shifters and tap changers with impedance correction tables, adding reactive power control and partitioning the grids into active and reactive reserve zones and determine different types of the required reserve for each zone. Hourly load time series at the bus level were generated to create scenarios for solving power flow in different loading conditions. Weather measurement information and the models of renewable generators are used to directly include the impact of weather on the grids. Based on a variety of load and weather conditions the grids are improved to accommodate different conditions. The ERCOT 7k-bus grids were also modeled for the year 2030 with predicted improvements in renewable resources. The renewable generation model was also improved with historic weather data included. The impact of electric vehicles on the ERCOT grid is also modeled.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Modeling and Market Design Considerations for Conventional and Decarbonized Resources

The following paper reviews various market design issues that will need to be reconsidered due to anticipated changes in the resources that supply energy in wholesale electricity markets. As the energy supply continues towards decarbonization, the change in resource technologies will affect the fundamentals of production scheduling and the policies to address supply variability and uncertainty. We show through simple numerical examples that the existing market design approach based on fuel costs will result in $0/MWh prices with intermittent price spikes during reserve shortages, but that incorporating more granular reserve pricing, energy storage participation, and price-responsive demand participation can restore efficient market clearing with reasonable pricing outcomes. The market design approach fundamentally shifts from fuel based to opportunity cost based. We briefly review alternative market design frameworks that can support this shift, including intraday markets, decentralized markets, flexibility options, and swing contracts. Market designs may also be required to accommodate or support various out-of-market policies and agreements; ideally, these external factors can be integrated into the market design to facilitate efficient exchanges across longer time scales, between other markets, and in support of public policy goals. The paper concludes by discussing how decarbonization trends may affect the design and use of production cost models for short term operations and long term planning studies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Task 12 PV Sustainability - Mineral Resource Use Footprints of Residential PV Systems

Resource use intensity is often mentioned as one of the main characteristics of PV systems and PV electricity. Recently, the International Energy Agency published a report on the role of critical minerals in clean energy transitions. The Product Environmental Footprint pilot study on PV electricity quantified (among other environmental impacts) its abiotic depletion potential. So far, a comprehensive assessment of resource use impacts highlighting the different facets of its impacts is however lacking. For the first time, the resource use impacts of PV electricity are quantified simultaneously with four impact category indicators recommended or suggested by the Life Cycle Initiative hosted at UN Environment. The indicators cover distinctly different aspects of resource use, namely resource depletion with the Abiotic Depletion Potential, ultimate reserves (ADP UR ), economic resource scarcity with the Abiotic Depletion Potential, economic reserves (ADP ER ), resource quality with the Surplus Ore Potential, Ultimate Recoverable Resources (SOP URR ) and re-source criticality with the ESSENZ method. The resource use impacts caused from the generation of 1 kWh electricity with a residential scale photovoltaic (PV) system installed in Central Europe using mono- and multi-crystalline silicon panels and CdTe panels, respectively are quantified. The product system includes manufacture, use and end of life treatment (take back and recycling) of the PV panels, cabling, inverter and supporting structure, the supply chains of the raw materials and energy used in PV panel and inverter manufacture as well as transport logistics.

14 SOLAR ENERGY↗
DOE OSTI2024

Solar and Storage Integration in the Southeastern United States: Economics, Reliability, and Operations

Solar energy has the potential to be a core energy resource for the southeastern United States. To better understand the implications of higher levels of solar PV (27%-43% of total generation capacity) and electricity storage (13%-49% of peak load) would affect electricity system reliability, costs, and operations in the U.S. Southeast, this study sought to address two main questions. First, how would higher levels of solar PV and electricity storage impact the costs, reliability, and operations of electricity systems in the Southeast in 2035? Second, at different levels of solar PV and electricity storage, what are the benefits of operational coordination among utilities in the Southeast, through more efficient regional dispatch and sharing operating reserves? To answer these questions, the study used detailed capacity expansion and dispatch modeling to develop and examine 15 scenarios with different levels of solar PV, electricity storage, and operational coordination, focusing on the year 2035. The study also evaluates the benefits of operational coordination among utilities through more efficient regional dispatch and reserve sharing, at different levels of solar and storage. The study focuses on five balancing regions that cover Alabama, Georgia, Kentucky, North Carolina, South Carolina, Tennessee, and parts of Mississippi and Missouri.

14 SOLAR ENERGY↗
DOE OSTI2024

Solar and Storage Integration in the Southeastern United States: Economics, Reliability, and Operations

Solar energy has the potential to be a core energy resource for the southeastern United States. To better understand the implications of higher levels of solar PV (27%-43% of total generation capacity) and electricity storage (13%-49% of peak load) would affect electricity system reliability, costs, and operations in the U.S. Southeast, this study sought to address two main questions. First, how would higher levels of solar PV and electricity storage impact the costs, reliability, and operations of electricity systems in the Southeast in 2035? Second, at different levels of solar PV and electricity storage, what are the benefits of operational coordination among utilities in the Southeast, through more efficient regional dispatch and sharing operating reserves? To answer these questions, the study used detailed capacity expansion and dispatch modeling to develop and examine 15 scenarios with different levels of solar PV, electricity storage, and operational coordination, focusing on the year 2035. The study also evaluates the benefits of operational coordination among utilities through more efficient regional dispatch and reserve sharing, at different levels of solar and storage. The study focuses on five balancing regions that cover Alabama, Georgia, Kentucky, North Carolina, South Carolina, Tennessee, and parts of Mississippi and Missouri.

14 SOLAR ENERGY↗
DOE OSTI2024

Bill Savings vs. Backup Power: Evaluating operational tradeoffs for home solar+storage systems [Slides]

Adoption of residential solar photovoltaic+energy storage systems (PVESS) is driven by both bill savings opportunities and customer demand for backup power. Prior work by this team (Gorman et al., 2022; Gorman et al., 2023) explored PVESS backup power capabilities during long-duration power interruptions (e.g., due to severe weather events), when customers are assumed to be able to anticipate the event and charge their batteries in advance. In many cases, however, power interruptions are unpredictable (and often relatively short); for those types of events, a customer will typically set its battery to maintain some minimum capacity in reserve in case of an interruption, which reduces the capacity available for managing utility bills. This study evaluates this operational tradeoff to help customers and installers configure backup reserve settings, and to inform decision-making more generally about the customer value of backup power services compared to utility bill savings. This study utilizes Berkeley Lab’s PRESTO tool to produce stochastic simulations of (predominantly short-duration) power interruption events, and builds on an earlier case-study demonstrating PVESS backup performance during short-duration interruptions (Baik et al., 2023).

14 SOLAR ENERGY↗
DOE OSTI2025

Hybrid Power Plants for Energy Resilience: A Case Study

As renewable energy technologies are increasingly adopted, they pose an opportunity to improve the sustainability and resilience of distributed grids, especially when their design and operation is coordinated as a hybrid power plant. When included in hybrid power plants, distributed wind turbines in particular have the potential to enhance the resilience of distributed grids in areas with good wind resource, due to their ability to provide more consistent generation and ancillary services as compared to photo-voltaic (PV) solar panels. Despite this benefit, U.S. distributed wind adoption is lower than other comparable renewable energy technologies. In this study, we seek to demonstrate how hybrid power plants that include distributed wind turbines can contribute to distribution grid resilience by meeting loads (especially critical loads) more consistently, increasing reserve capacity, and providing value to customers during outages. To demonstrate these contributions, we integrate three separate frameworks and apply them to a case study in a rural electric cooperative in Iowa. Through this case study, we simulate and compare hybrid power plant design and operation during two hazard events: a tornado that causes a 48-hour distribution outage and a winter weather event that causes a 6-hour generation outage. The inclusion of a hybrid power plant that leverages 1) increased battery duration and 2) advanced forecasting and dispatch strategies that reserve capacity leading up to a hazard event best reduce lost loads as well as diesel consumption that would otherwise be used to meet those loads during short- and long-duration hazard events. Depending on the hybrid power plant capacity and operation, we find that the outage mitigation value of a hybrid power plant (measured in value to customers to avoid an outage and avoided lost revenues for the utility) is significant in both hazard events; adding wind, solar, and battery assets to the existing system adds about $50-$100M in avoided lost load and at least $4-$8k in utility value in the tornado hazard event, and $570k-$2.2M in avoided lost load and at least $220-$650 in utility value in the winter hazard scenario. In both the tornado and winter hazard scenarios, optimizing the operation of the hybrid system for resilience can lend similar value as increasing battery duration by 5 MWh for the lower capacity systems considered.

17 WIND ENERGY↗
DOE OSTI2025

Enhanced Outcrop Methane Capture (Final Project Report)

This report provides the final status of the “Enhanced Outcrop Methane Capture (EOMC) Project” which was focused on drilling two new methane capture wells along the Fruitland Formation Outcrop for capture of methane and carbon dioxide which are naturally seeping from the Outcrop. The EOMC Project was focused on evaluating whether novel horizontal drilling technology will result in improved capture of methane and carbon dioxide which are naturally seeping from the Fruitland Formation Outcrop on Southern Ute tribal trust lands within the Southern Ute Indian Reservation (the “Reservation”).

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Section 3 Reporting: Preserve America

Brookhaven National Laboratory (BNL) is a multidisciplinary laboratory with seven Nobel Prize-winning discoveries, 37 R&D 100 Awards, and countless advances in science and technology. For over 75 years, the Laboratory has played a leading role in the Department of Energy (DOE) Science and Technology mission and continues to contribute to the DOE’s missions in energy resources, environmental quality, and national security. The Laboratory is operated and managed by Brookhaven Science Associates (BSA), which was founded by the Research Foundation for the State University of New York on behalf of Stony Brook University, and Battelle, a non-profit applied science and technology organization. BNL is committed to longstanding partnerships with researchers, academic institutions, industry, students, teachers, and the surrounding community. BNL is located near the center of Suffolk County on Long Island, New York within Brookhaven Township, about 60 miles east of New York City. Most of BNL’s principal facilities are located near the center of the 5,265-acre (8.23 square mile) site (Figure 1). The developed area encompasses approximately 1,820 acres, consisting of: ▪ 500 acres originally developed by the Army (as part of WW II Camp Upton) and still used for offices and other operational buildings. ▪ 200 acres occupied by large, specialized research facilities. ▪ 520 acres occupied by outlying facilities, such as the Sewage Treatment Plant, research agricultural fields, housing facilities, and fire breaks. ▪ 400 acres of roads, parking lots, and connecting areas. ▪ 200 acres developed for the Long Island Solar Farm. The balance of the site, approximately 3,400 acres, is largely wooded and represents a native pine barrens ecosystem. In November 2000, DOE set aside 530 acres of undeveloped land at BNL as the Upton Ecological and Research Reserve. The Upton Reserve preserves this portion of the pine barrens ecosystem and provides an area for ecological research and education activities.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Ch3MS-RF: a random forest model for chemical characterization and improved quantification of unidentified atmospheric organics detected by chromatography–mass spectrometry techniques

Abstract. The chemical composition of ambient organic aerosols plays a critical role in driving their climate and health-relevant properties and holds important clues to the sources and formation mechanisms of secondary aerosol material. In most ambient atmospheric environments, this composition remains incompletely characterized, with the number of identifiable species consistently outnumbered by those that have no mass spectral matches in the literature or the National Institute of Standards and Technology/National Institutes of Health/Environmental Protection Agency (NIST/NIH/EPA) mass spectral databases, making them nearly impossible to definitively identify. This creates significant challenges in utilizing the full analytical capabilities of techniques which separate and generate spectra for complex environmental samples. In this work, we develop the use of machine learning techniques to quantify and characterize novel, or unidentifiable, organic material. This work introduces Ch3MS-RF (Chemical Characterization by Chromatography–Mass Spectrometry Random Forest Modeling), an open-source, R-based software tool, for efficient machine-learning-enabled characterization of compounds separated in chromatography–mass spectrometry applications but not identifiable by comparison to mass spectral databases. A random forest model is trained and tested on a known 130 component representative external standard to predict the response factors of novel environmental organics based on position in volatility–polarity space and mass spectrum, enabling the reproducible, efficient, and optimized quantification of novel environmental species. Quantification accuracy on a reserved 20 % test set randomly split from the external standard compound list indicates that random forest modeling significantly outperforms the commonly used methods in both precision and accuracy, with a median response factor percent error of −2 %, for modeled response factors, compared to > 15 %, for typically used proxy assignment-based methods. Chemical properties modeling, evaluated on the same reserved 20 % test set and an extrapolation set of species identified in ambient organic aerosol samples collected in the Amazon rainforest, also demonstrate robust performance. Extrapolation set property prediction mean absolute errors for carbon number, oxygen to carbon ratio (O : C), average carbon oxidation state (OSc‾), and vapor pressure are 1.8, 0.15, 0.25, and 1.0 (log(atm)), respectively. Extrapolation set out-of-sample R2 for all properties modeled are above 0.75, with the exception of vapor pressure. While predictive performance for vapor pressure is less robust compared to the other chemical properties modeled, random-forest-based modeling was significantly more accurate than other commonly used methods of vapor pressure prediction, decreasing the mean vapor pressure prediction error to 0.24 (log(atm)) from 0.55 (log(atm)) (chromatography-based vapor pressure prediction) and 1.2 (log(atm)) (chemical formula-based vapor pressure prediction). The random forest model significantly advances an untargeted analysis of the full scope of chemical speciation yielded by two-dimensional gas chromatography (GCxGC-MS) techniques and can be applied to gas chromatography coupled with electron ionization mass spectrometry (GC-MS) as well. It enables the accurate estimation of key chemical properties commonly utilized in the atmospheric chemistry community, which may be used to more efficiently identify important tracers for further individual analysis and to characterize compound populations uniquely formed under specific ambient conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Technical note: A modified formulation of dynamic energy budget theory for faster computation of biological growth

Abstract. The mass conservation equation in the presence of boundary fluxes and chemical reactions from non-equilibrium thermodynamics is used to derive a modified dynamic energy budget (mDEB) model. Compared to the standard dynamic energy budget (sDEB) model (Kooijman, 2009), this modified formulation does not place the dilution effect in the mobilization kinetics of reserve biomass, and it maintains the partition principle for reserve mobilization dynamics for both linear and non-linear kinetics. Overall, the mDEB model shares most features with the sDEB model. However, for biological growth that requires multiple nutrients, the mDEB model is computationally much more efficient by not requiring numerical iterations for obtaining the specific growth rate. In an example of modeling the growth of Thalassiosira weissflogii in a nitrogen-limiting chemostat, the mDEB model was found to have almost the same accuracy as the sDEB model while requiring almost half of the computing time of the sDEB model. Since the sDEB model has been successfully applied in numerous studies, we believe that the mDEB model can help improve the modeling of biological growth and the associated ecosystem processes in various contexts.

Tang, Jinyun↗
DOE OSTI2023

CORPSE model with litter decomposition parameters derived from the LIDET dataset

This is a version of the CORPSE model (Carbon, Organisms, Rhizosphere and Protection in the Soil Environment, Sulman et al. 2014) that uses litter decomposition parameters derived from a modified Monte Carlo simulation using the LIDET litter decomposition dataset (Long-term Intersite Decomposition Experiment Team, Harmon 2013). The code also includes the Baseline parameters, and the eight other best parameter sets identified in a modified Monte Carlo simulation. Related publication:Juice, S.M., Ridgeway, J.R., Hartman, M.D., Parton, W.J., Berardi, D.M., Sulman, B.N., Allen, K.E., & Brzostek, E.R. Reparameterizing litter decomposition using a simplified Monte Carlo method improves litter decay simulated by a microbial model and alters bioenergy soil carbon estimates. Description of files:The folder "Input Files" contains one folder for each LIDET site with data necessary to run the model. Note that "(site)" in the filenames below indicates where the LIDET site code appears (see Table 1 for site codes). Data streams include: CORPSE_full_spinup_litter.csv, CORPSE_full_spinup_rhizo.csv, CORPSE_full_spinup_bulk.csv, litterbag_init_100g_6spp.csv: initial C and N (kg C or N/m2) pool values for each soil layer, the litterbag_init_100_6spp.csv file is for the litterbag layer and is the same file for all sites. All initial C and N files have the same columns (Column - Description - Units) uFastC - Unprotected fast decomposing carbon - kg carbon/m2 uSlowC - Unprotected slow decomposing carbon - kg carbon/m2 uNecroC - Unprotected necromass carbon - kg carbon/m2 pFastC - Protected fast decomposing carbon - kg carbon/m2 pSlowC - Protected slow decomposing carbon - kg carbon/m2 pNecroC - Protected necromass carbon - kg carbon/m2 livingMicrobeC - Carbon in living microbial biomass - kg carbon/m2 uFastN - Unprotected fast decomposing nitrogen - kg nitrogen/m2 uSlowN - Unprotected slow decomposing nitrogen - kg nitrogen/m2 uNecroN - Unprotected necromass nitrogen - kg nitrogen/m2 pFastN - Protected fast decomposing nitrogen - kg nitrogen/m2 pSlowN - Protected slow decomposing nitrogen - kg nitrogen/m2 pNecroN - Protected necromass nitrogen - kg nitrogen/m2 inorganicN - Inorganic nitrogen - kg nitrogen/m2 CO2 - Carbon in carbon dioxide - kg carbon/m2 livingMicrobeN - Nitrogen in living microbial biomass - kg nitrogen/m2 soilT (site) DOY274start.csv: Average daily soil temperature (oC) interpolated from previously calculated monthly values used in DayCent LIDET simulations (Bonan et al., 2013). soilT (site) DOY274start.csv: Average daily soil volumetric water content (VWC) scalar interpolated from previously calculated monthly values used in DayCent LIDET simulations (Bonan et al., 2013). litter production.csv: Average daily litter production values for each site, data sources listed in Table S3 of related publication. litter (site) CN.csv: C:N ratio for each species from LIDET dataset (Table 2, Harmon 2013). (site).csv: Table indicating number of observations for each species decomposed at each site. Instructions: Save the model code ("CORPSE_LIDET.R") and "Input Files" folder in the same folder. Also make a folder for the model output (e.g., "results_Baseline") in the same folder. Set the working directory (setwd) in the model code to the folder with the files saved in step #1. Select the parameter set to use for the litter and litterbag compartments, comment out all other parameter sets. Run code. Output will be saved in the folder made in step 1. Output destination can be changed as necessary in code section called "Running the model." Table 1 LIDET sites and site codes used in model files. Site Code - Site AND - H.J. Andrews Experimental Forest BNZ - Bonanza Creek Experimental Forest BSF - Blodgett Research Forest CDR - Cedar Creek Natural History Area CPR - Central Plains Experimental Range HBR - Hubbard Brook Experimental Forest HFR - Harvard Forest JUN - Juneau KBS - Kellogg Biological Station KNZ - Konza Prairie Research Natural Area NWT - Niwot Ridge/Green Lakes Valley OLY - Olympic National Park OLY Conifer forest SEV - Sevilleta National Wildlife Refuge SMR - Santa Margarita Ecological Reserve UFL - University of Florida VCR - Virginia Coast Reserve Table 2 LIDET species and species codes used in model files (6 common species). Species - Species Code Sugar maple (Acer saccharum) - ACSA Drypetes (Drypetes glauca) - DRGL Red pine (Pinus resinosa) - PIRE Chestnut oak (Quercus prinus) - QUPR Western redcedar (Thuja plicata) - THPL Wheat (Triticum aestivum) - TRAE References:Bonan, G. B., Hartman, M. D., Parton, W. J., & Wieder, W. R. (2013). Evaluating litter decomposition in earth system models with long-term litterbag experiments: an example using the Community Land Model version 4 (CLM4). Global Change Biology, 19(3), 957-974. https://doi.org/https://doi.org/10.1111/gcb.12031 Harmon, M. (2013). LTER Intersite Fine Litter Decomposition Experiment (LIDET), 1990 to 2002. Long-Term Ecological Research. Forest Science Data Bank, Corvallis, OR. [Data set]. Accessed http://andlter.forestry.oregonstate.edu/data/abstract.aspx?dbcode=TD023. https://doi.org/10.6073/pasta/f35f56bea52d78b6a1ecf1952b4889c5. Sulman, B. N., Phillips, R. P., Oishi, A. C., Shevliakova, E., & Pacala, S. W. (2014). Microbe-driven turnover offsets mineral-mediated storage of soil carbon under elevated CO2. Nature Climate Change, 4, 1099 - 1102. https://doi.org/10.1038/nclimate2436

Juice, Stephanie↗
NASA NTRS1975

Hydrogen production econometric studies

The current assessments of fossil fuel resources in the United States were examined, and predictions of the maximum and minimum lifetimes of recoverable resources according to these assessments are presented. In addition, current rates of production in quads/year for the fossil fuels were determined from the literature. Where possible, costs of energy, location of reserves, and remaining time before these reserves are exhausted are given. Limitations that appear to hinder complete development of each energy source are outlined.

Howell, J. R.↗
NASA NTRS1980

Packet communications in satellites with multiple-beam antennas and signal processing

A communication satellite with a multiple-beam antenna and onboard signal processing is considered for use in a 'message-switched' data relay system. The signal processor may incorporate demodulation, routing, storage, and remodulation of the data. A system user model is established and key functional elements for the signal processing are identified. With the throughput and delay requirements as the controlled variables, the hardware complexity, operational discipline, occupied bandwidth, and overall user end-to-end cost are estimated for (1) random-access packet switching; and (2) reservation-access packet switching. Other aspects of this network (eg, the adaptability to channel switched traffic requirements) are examined. For the given requirements and constraints, the reservation system appears to be the most attractive protocol.

Davies, R.↗
NASA NTRS1980

Regional price targets appropriate for advanced coal extraction

A methodology is presented for predicting coal prices in regional markets for the target time frames 1985 and 2000 that could subsequently be used to guide the development of an advanced coal extraction system. The model constructed is a supply and demand model that focuses on underground mining since the advanced technology is expected to be developed for these reserves by the target years. Coal reserve data and the cost of operating a mine are used to obtain the minimum acceptable selling price that would induce the producer to bring the mine into production. Based on this information, market supply curves can be generated. Demand by region is calculated based on an EEA methodology that emphasizes demand by electric utilities and demand by industry. The demand and supply curves are then used to obtain the price targets. The results show a growth in the size of the markets for compliance and low sulphur coal regions. A significant rise in the real price of coal is not expected even by the year 2000. The model predicts heavy reliance on mines with thick seams, larger block size and deep overburden.

Terasawa, K. L.↗
NASA NTRS1983

Phosphoric acid fuel cell platinum use study

The U.S. Department of Energy is promoting the private development of phosphoric acid fuel cell (PAFC) power plants for terrestrial applications. Current PAFC technology utilizes platinum as catalysts in the power electrodes. The possible repercussions that the platinum demand of PAFC power plant commercialization will have on the worldwide supply and price of platinum from the outset of commercialization to the year 2000 are investigated. The platinum demand of PAFC commercialization is estimated by developing forecasts of platinum use per unit of generating capacity and penetration of PAFC power plants into the electric generation market. The ability of the platinum supply market to meet future demands is gauged by assessing the size of platinum reserves and the capability of platinum producers to extract, refine and market sufficient quantities of these reserves. The size and timing of platinum price shifts induced by the added demand of PAFC commercialization are investigated by several analytical methods. Estimates of these price shifts are then used to calculate the subsequent effects on PAFC power plant capital costs.

Lundblad, H. L.↗
NASA NTRS1985

Vector computer memory bank contention

A number of vector supercomputers feature very large memories. Unfortunately the large capacity memory chips that are used in these computers are much slower than the fast central processing unit (CPU) circuitry. As a result, memory bank reservation times (in CPU ticks) are much longer than on previous generations of computers. A consequence of these long reservation times is that memory bank contention is sharply increased, resulting in significantly lowered performance rates. The phenomenon of memory bank contention in vector computers is analyzed using both a Markov chain model and a Monte Carlo simulation program. The results of this analysis indicate that future generations of supercomputers must either employ much faster memory chips or else feature very large numbers of independent memory banks.

Bailey, D. H.↗
NASA NTRS1984

An integrated voice and data multiple-access scheme for a land-mobile satellite system

An analytical study is performed of the satellite requirements for a land mobile satellite system (LMSS). The spacecraft (MSAT-X) would be in GEO and would be compatible with multiple access by mobile radios and antennas and fixed stations. The FCC has received a petition from NASA to reserve the 821-825 and 866-870 MHz frequencies for the LMSS, while communications with fixed earth stations would be in the Ku band. MSAT-X transponders would alter the frequencies of signal and do no processing in the original configuration considered. Channel use would be governed by an integrated demand-assigned, multiple access protocol, which would divide channels into reservation and information channels, governed by a network management center. Further analyses will cover tradeoffs between data and voice users, probability of blocking, and the performance impacts of on-board switching and variable bandwidth assignment. Initial calculations indicate that a large traffic volume can be handled with acceptable delays and voice blocking probabilities.

Li, V. O. K.↗