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1,068 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

A Comparison of GoldSim, RESRAD-Onsite, and NORMALYSA Modeling Tools at Radioactive Waste Sites - 19480

Radioactive waste disposal and associated decision making is a challenging problem around the world. A strong performance assessment model plays a crucial role in making good management and remediation decisions and in optimizing the performance of a site. The International Atomic Energy Agency (IAEA) MODARIA II Working Group 1 (WG1) is comparing the performance of various modeling platforms used at Naturally Occurring Radioactive Material (NORM) and legacy waste sites to support risk-informed decision making. Neptune and Company, Inc. (Neptune) has developed probabilistic performance assessment models using the GoldSim system modeling software at a variety of radioactive waste sites. This paper presents a comparison between GoldSim and two other tools used to evaluate radiation exposure and their associated risks: the NORM And Legacy Site Assessment (NORMALYSA) tool used to assess risk at the Zapadnoe mill tailings site, and the residual radioactivity (RESRAD-Onsite) computer program used to calculate Authorized Limits at the Los Alamos National Laboratory (LANL). The International Atomic Energy Agency (IAEA) supported development of NORMALYSA based off of Ecolego 6.0, in which the user connects several universal modules, representing various environmental transport and exposure pathways, and enters in site-specific data. Further work with NORMALYSA has continued under the MODARIA II WG 1. A radionuclide transport and dose calculation model of the Zapadnoe uranium mill tailings site at the Pridneprovsky Chemical Plant in the Ukraine has been configured by MODARIA II WG1 to test the capabilities of NORMALYSA. Under this test case, contaminant transport and effective dose calculations were performed for two exposure scenarios. The onsite worker is exposed via external ground irradiation and radon and radioactive dust inhalation. The offsite resident defines a residence established 300 years after institutional control has ended, 800 meters downstream from the site with exposure pathways including: ingestion of garden vegetables irrigated by contaminated ground water, ingestion of fish from the Konoplyanka River and agricultural activities in the contaminated garden. GoldSim modeling software is a dynamic probabilistic modeling platform that evaluates uncertainty in a robust and transparent manner. Although GoldSim provides contaminant and radionuclide transport modules to facilitate integrated modeling of radionuclide migration in the environment, these features are not embedded in an existing modeling framework, except as created by the user. Neptune developed a GoldSim model for the two exposure scenarios of the Zapadnoe test case. Neptune's Generic PA Model was used as a starting point for the Zapadnoe site. Input parameters for the GoldSim model include site-specific parameters from the MODARIA Working Group as well as parameters from the Generic PA Model and other PA models created by Neptune. For the other comparison, Version 7.0 of RESRAD-Onsite, developed by Argonne National Laboratory for the U.S. Department of Energy (DOE), was used to calculate Authorized Limits for LANL. Authorized Limits are concentrations of radionuclides in soil that support the evaluation process to clear land for release under different uses. The RESRAD-Onsite computer code was used to calculate Authorized Limits because this program was specifically designed to derive radionuclide soil guidelines corresponding to a specific dose criterion. The scope of the RESRAD dose or risk evaluation is constrained to the transport and exposure pathways that have been included in the computer code. To assist in illustrating the capability of GoldSim modeling software, a GoldSim model was created to replicate the calculation of LANL's Authorized Limits for soil. The main exposure pathways in this model are inhalation of dust and gas, plant ingestion, soil ingestion, and external ground irradiation. All of the processes and outputs of RESRAD-Onsite and NORMALYSA can be created in a GoldSim model, but the value of GoldSim lies in its flexibility for application to any of a wide variety of environmental modeling problems. GoldSim allows development of site-specific inventory, transport mechanisms and risk assessment scenarios. If all potentially complete release, transport, and exposure pathways are addressed in an existing dose and risk assessment computer code, and if the code's capabilities fulfill the project modeling objectives, then expending resources to create a GoldSim model may not be necessary. Site optimization and good decision making about site management are often best when supported with the flexibility of GoldSim as a modeling tool. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Sun Grant/DOE Regional Feedstock Partnership: Final Technical Report

The U.S. Department of Energy (DOE) and the Sun Grant Initiative initiated the Regional Feedstock Partnership (referred to as the Partnership) in 2007 primarily to address information gaps associated with the likelihood for realization of the sustainable and reliable production of a billion-tons of biomass annually to support the U.S. bioenergy industry by the year 2030. Publication of The Technical Feasibility of a Billion-Ton Annual Supply (Perlack et al., 2005) in 2005, with its associated yield assumptions, led to the realization that the yield goals and assumptions utilized in that analysis required careful validation. To achieve the overall goal of validating key yield assumptions, the following objectives were developed: 1. Establishment of replicated field trials across regions to determine the impact of crop residue removal (primarily corn and small grains) on future grain yields and soil health. 2. Establishment of replicated field trials of some of the most promising dedicated energy crops (herbaceous annuals and perennials, as well as woody perennials) to demonstrate the potential performance of these feedstocks across the U.S. 3. Assessment of feedstock resources to be used to estimate a sustainable national supply potential. Teams composed of representatives from Land Grant Universities, USDA ARS, DOE National Laboratories, industry, and other federal agencies were identified and assembled to address each of these objectives. For Objective 1, members of the USDA ARS’ Resilient Economic Agricultural Practices (REAP) team combined with university personnel to leverage on-going work and established new trials to determine sustainable corn residue removal rates. In addition, universities across the continental U.S. conducted surveys of published past research to define parameters for the use of cereal grain residue (primarily wheat) as a biomass feedstock. For Objective 2, and based on input from DOE, USDA, Land Grant university scientists, and others, several herbaceous and woody energy crop species were selected for new or further evaluation across wide geographic areas as cellulosic feedstock sources. Species teams were organized to assess the yield potential of candidate herbaceous feedstocks including sorghum, energycane, Miscanthus x giganteus (hereafter referred to as miscanthus), switchgrass, and mixed perennial species (primarily grasses and some legumes) on Conservation Reserve Program (CRP) land. Woody species will be critical components of the bioenergy sector; therefore, species teams were also organized for shrub willow and hybrid poplar (Populus spp.). Field trials of each species were utilized to determine yield potential across the U.S. For Objective 3, a GIS resource team was organized with representatives from each of the five Sun Grant regions. While some regional assessments were made, the multi-institutional team decided that the group from Oregon State University would utilize their PRISM ELM model to estimate national yield potential of the various species evaluated. The following are key outcomes and impacts • The Partnership demonstrated the production potential of diverse herbaceous and woody feedstocks across much of the U.S. for 5-7 consecutive growing seasons. Long-term studies such as this are not commonly possible due to limitations in funding cycles. • Long-term field trials were valuable in demonstrating the importance of agronomic management practices and genetic resources to yield of sorghum, switchgrass, miscanthus, energycane, CRP mixed perennial grasses, poplar, and willow. • National yield potential maps were developed for all species evaluated in the Partnership. • Sustainable corn stover removal rates were quantified for use by producers, harvesters, and commercial lignocellulosic biorefineries. • Data from the Partnership field trials not only validated initial Billion Ton estimates, but were instrumental in developing both the Billion Ton Update in 2011, and especially the 2016 Billion Ton Report. • The Partnership provided the opportunity to assemble and conserve a poplar germplasm collection that contains more than 20,000 clones for use in breeding programs. New clones resulting from crosses made using this germplasm collection have resulted in significantly improved cultivars that could be scaled up and deployed. • Further validation of improved yields of new varieties/cultivars of biomass sorghum, energycane, hybrid poplars, and shrub willows was produced by the Partnership. • The Partnership demonstrated the potential of energycane in northern parts of the southeastern U.S., particularly in relation to sugarcane varieties. • For certain feedstocks (e.g., CRP mixed grasses, switchgrass, willow, and poplar), production economics were ascertained through Partnership field trials. • Biomass samples collected as part of the Partnership are also being used to populate Idaho National Laboratory’s Bioenergy Feedstock Library. • Because of the size and scope of the Partnership, workforce development was a key component and outcome. Numerous undergraduate students (25), graduate students (15 MS and 8 PhD), and postdoctoral researchers (7) were trained by Partnership participants. This will help to prepare individuals for careers in the emerging fields of plant breeding, biomass production, feedstock supply logistics, and biomass conversion processes. • More than 130 scientific publications have been authored by Partnership team members. Numerous other presentations, outreach publications, book chapters, and websites have also been developed to further the continued development of the bioeconomy.

09 BIOMASS FUELS↗
DOE OSTI2018

A Scaling Study of Microbially-Enhanced Methane Production From Coal (Mecbm): Optimizing Nutrient Delivery For Maximized Methane Production

Microbially-enhanced coalbed methane (MECBM) recovery is a novel method to stimulate gas production in CBM reservoirs. We first develop suitable nutrient recipes for native coals from sites each in the Illinois Basin and in the San Juan Basin. The optimal concentrations for statistically significant parameters are identified and the methane yields at laboratory scale are obtained (Part I & II). We then demonstrate the importance of replicating truly in-situ conditions for bio- gasification studies by investigating methane productivity in a core holder simulating in-situ conditions. Based on the experimental results, the resulting gas production correlates positively with the permeability of the samples. We examine the deliverability of engineered microbial solutions to promote coal bioconversion in coals and demonstrate that greater than milli-darcy permeability is required under in-situ stress conditions (Part III). This constraint is supplemented by imaging and a fractal-based characterization approach to evaluate changes in the physical properties of coal due to bio-gasification. High resolution SEM imaging is used to observe swelling of the coal matrix with sub-micron wide continuous pores observed to persist even after microbial treatment (IV). We explore the potential of generating, propping-open and sustaining the functionality of hydraulic fractures in coal using different fracturing fluids (Part V). The alteration of the nano-pore structure due to MECBM treatment is examined by using small angle X-ray scattering (SAXS) to define the in-situ porosity evolution as a proxy to infer permeability evolution (Part VI). Coupled hydro-mechanical and bio-gasification modeling is applied to determine the effectiveness of nutrient delivery by hydraulic fracturing and its field implementation. Compared with both the unstimulated and hydro-shear-dilated cases of the natural fracture network, hydraulic fracturing demonstrates a significant improvement to enhance nutrient delivery. A preliminary analysis of field-scale methane yield is completed with consideration of the combined influence of permeability evolution, solute transport and microbial growth (Part VII). Developing nutrient solutions for Illinois Basin and San Juan Basin (Task 2): To enhance methane release from coal through bio-gasification, suitable nutrient solutions are needed to stimulate microbial activities toward coal depolymerization and conversion to biogas. Specific for bituminous coal in the Illinois basin, a nutrient recipe that can be used to enhance coal bio- gasification in situ is developed. Based on our previous experience working with Illinois coal and the characteristics of the formation water and the indigenous microbial community, four parameters, Fe powder, methanol, ethanol, and trace minerals are optimized through using a Box-Behnken design. The optimal condition predicted by the models is: Fe-powder at 74 mM, methanol at 97.91 mM, ethanol at 100 mM, and trace minerals at 100%. Under these conditions, the predicted methane yield and content is 1,417.35 ft 3 /ton and 80.7%, respectively. These results are then validated by experimental studies. In addition, each added component is evaluated in terms of its contribution to methane generated. Specifically, the role of coal in the bio-gasification process is studied against two other solid materials. Experimental data from different solid matrices prove that coal is indeed degraded by the studied microbial community.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

ON-OFF neuromorphic ISING machines using Fowler-Nordheim annealers

We introduce NeuroSA, a neuromorphic architecture specifically designed to ensure asymptotic convergence to the ground state of an Ising problem using a Fowler-Nordheim quantum mechanical tunneling based threshold-annealing process. The core component of NeuroSA consists of a pair of asynchronous ON-OFF neurons, which effectively map classical simulated annealing dynamics onto a network of integrate-and-fire neurons. The threshold of each ON-OFF neuron pair is adaptively adjusted by an FN annealer and the resulting spiking dynamics replicates the optimal escape mechanism and convergence of SA, particularly at low-temperatures. To validate the effectiveness of our neuromorphic Ising machine, we systematically solved benchmark combinatorial optimization problems such as MAX-CUT and Max Independent Set. Across multiple runs, NeuroSA consistently generates distribution of solutions that are concentrated around the state-of-the-art results (within 99%) or surpass the current state-of-the-art solutions for Max Independent Set benchmarks. Furthermore, NeuroSA is able to achieve these superior distributions without any graph-specific hyperparameter tuning. For practical illustration, we present results from an implementation of NeuroSA on the SpiNNaker2 platform, highlighting the feasibility of mapping our proposed architecture onto a standard neuromorphic accelerator platform.

42 ENGINEERING↗
DOE OSTI2019

Producing a BOSS CMASS sample with DES imaging

We present a sample of galaxies with the Dark Energy Survey (DES) photometry that replicates the properties of the BOSS CMASS sample. The CMASS galaxy sample has been well characterized by the Sloan Digital Sky Survey (SDSS) collaboration and was used to obtain the most powerful redshift-space galaxy clustering measurements to date. A joint analysis of redshift-space distortions (such as those probed by CMASS from SDSS) and a galaxy-galaxy lensing measurement for an equivalent sample from DES can provide powerful cosmological constraints. Unfortunately, the DES and SDSS-BOSS footprints have only minimal overlap, primarily on the celestial equator near the SDSS Stripe 82 region. Using this overlap, we build a robust Bayesian model to select CMASS-like galaxies in the remainder of the DES footprint. The newly defined DES-CMASS (DMASS) sample consists of 117,293 effective galaxies covering $1,244 {\rm deg}^2$. Through various validation tests, we show that the DMASS sample selected by this model matches well with the BOSS CMASS sample, specifically in the South Galactic cap (SGC) region that includes Stripe 82. Combining measurements of the angular correlation function and the clustering-z distribution of DMASS, we constrain the difference in mean galaxy bias and mean redshift between the BOSS CMASS and DMASS samples to be $\Delta b = 0.010^{+0.045}_{-0.052}$ and $\Delta z = \left( 3.46^{+5.48}_{-5.55} \right) \times 10^{-3}$ for the SGC portion of CMASS, and $\Delta b = 0.044^{+0.044}_{-0.043} $ and $\Delta z= ( 3.51^{+4.93}_{-5.91}) \times 10^{-3}$ for the full CMASS sample. These values indicate that the mean bias of galaxies and mean redshift in the DMASS sample is consistent with both CMASS samples within $1\sigma$.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗