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At least 487 records · Page 27

Efficient Optimization of Energy Recovery From Geothermal Reservoirs With Recurrent Neural Network Predictive Models

Improving the long-term energy production performance of geothermal reservoirs can be accomplished by optimizing field development and management plans. Reliable prediction models, however, are needed to evaluate and optimize the performance of the underlying reservoirs under various operation and development strategies. In traditional frameworks, physics-based simulation models are used to predict the energy production performance of geothermal reservoirs. However, detailed simulation models are not trivial to construct, require a reliable description of the reservoir conditions and properties, and entail high computational complexity. Data-driven predictive models can offer an efficient alternative for use in optimization workflows. This paper presents an optimization framework for net power generation in geothermal reservoirs using a variant of the recurrent neural network (RNN) as a data-driven predictive model. The RNN architecture is developed and trained to replace the simulation model for computationally efficient prediction of the objective function and its gradients with respect to the well control variables. The net power generation performance of the field is optimized by automatically adjusting the mass flow rate of production and injection wells over 12 years, using a gradient-based local search algorithm. Two field-scale examples are presented to investigate the performance of the developed data-driven prediction and optimization framework. Furthermore, the prediction and optimization results from the RNN model are evaluated through comparison with the results obtained by using a numerical simulation model of a real geothermal reservoir.

15 GEOTHERMAL ENERGY↗

Measurement of the angular dependence of the spontaneous Raman scattering in anisotropic crystalline materials using spherical samples: Potassium dihydrogen phosphate as a case example

A specialized experimental configuration was created to allow for more-accurate characterization of the spontaneous Raman scattering properties in anisotropic materials. This need stems from the challenges, arising from the complexity of light propagation, in obtaining accurate measurements of the angular dependence of the Raman scattering cross section in birefringent materials. The nonlinear optical material KH 2 PO 4 (KDP) is used as a model medium. Our report is motivated by the need to improve our understanding and management of transverse stimulated Raman scattering in KDP crystals and its deuterated analog, DKDP, typically used for frequency conversion and polarization control in large-aperture laser systems. Key to this experimental platform is the use of high-quality spherical samples that enable one to measure the Raman scattering cross section in a wide range of geometries using only a single sample. The effect of polarization rotation of both the pump light and the collected Raman signal must be carefully considered in data analysis and can give rise to artifacts, which can, in part, be mitigated by reducing the input and collection cone angles.

47 OTHER INSTRUMENTATION↗

EAM-X Potential Generator

SAND2023-06608O The EAM-X Potential Generator code establishes parameters that describe interactions between atoms in pure metals and alloys. The open-source software allows for the understanding of the relationship between general properties of atoms and macroscopic properties of metals. The code reads in values for the parameters of the model and outputs a table that describes the interactions. This code will be published by Acta Materialia along with two papers describing the method. The output of this code is meant for use by the LAMMPS simulation code created by Sandia. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Chandross, Michael↗

A Taxonomic Classification Approach for Global Spatio-temporal Data

The World Bank, World Health Organization, and other major vendors collectively provide thousands of global time series datasets that focus on issues of the environment, public health, economics, violence, education, and national security. Sorting these data into meaningful information requires the use of data mining techniques to cluster trends into an orderly and manageable number of cases. The World SpatioTemporal Analytics and Mapping (WSTAMP) project database (wstamp.ornl.gov) was developed to spatiotemporally harmonize global vendor data (23,300+ attributes, 200+ locations, 50+ years). Within the WSTAMP analytical environment, Dynamic Time Warping (DTW) has been a highly effective data-driven approach for clustering and mapping these time series into national spatiotemporal behavior maps. Two significant properties have surfaced from this work. First, several recognizable cluster patterns have emerged and persist across a range of locations, attributes, and time frames (e.g., increasing, decreasing, rebounding, peak, oscillating). Secondly, practitioners engaging WSTAMP have noted the explanatory and anticipatory value of these patterns and articulated particular interest in detecting them within the spatiotemporal cube. This need was addressed by shifting DTW-based clustering from an open ended, data-driven implementation to a taxonomic pattern matching approach. This paper presents the method including implementation strategies for visualization and human computer interaction and applies the approach to a sample data set and concludes with next steps.

Stewart, Robert↗

Enhanced Hanford Low-Activity Waste Glass Property Data Development (Phase 3)

This work was performed for the U.S. Department of Energy (DOE) Office of River Protection (ORP) to provide expert evaluation and experimental work in support of the River Protection Project vitrification technology development1. The long-term objective of this work is to expand the property-composition database for Hanford site low-activity waste (LAW) glasses and property-composition models to cover the balance of the mission for the Hanford Waste Treatment and Immobilization Plant (WTP). When this effort is complete, enhanced LAW glass property-composition models will be developed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Fundamental Studies of Tritium Formation and Diffusivity in Pure and Defective Zircaloy-4 Getters

Zirconium (Zr) and its alloys are used as fuel cladding in nuclear reactors. These materials have their low absorption cross-section for thermal neutrons and have good mechanical and thermal properties. In addition, they are used as tritium getters in tritium-producing burnable absorber rods (TPBARs), in the form of nickel-plated Zircaloy-4 tubes. To produce 3 H, the breading blankets such as lithium aluminate are irradiated in pressurized water. 3 H produced in this process is captured by the getter and 3 H reacts chemically with Zr to form metal hydride (ZrTx). The precipitation of metal hydride results in not only the volume increase and hydrogen embrittlement of zircaloy but also changes in getter’s chemical properties. This degrades the getter’s performance. Therefore, understanding the behavior of 3 H (such as diffusion and solubility) in zircaloy is important to understand getter performance.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Radioiodine sorbent selection criteria

Methods for preventing radioiodine from entering the environment are needed in processes related to nuclear energy and medical isotope production. The development and performance of many different types of sorbents to capture iodine have been reported on for decades; however, there is yet to be a concise overview on the important parameters that should be considered when selecting a material for chemically capturing radioiodine. This paper summarizes several criteria that should be considered when selecting candidate sorbents for implementation into real-world systems. The list of selection criteria discussed are 1) optimal capture performance, 2) kinetics of adsorption, 3) performance under relevant process conditions, 4) properties of the substrate that supports the getter, and 5) environmental stability and disposition pathways for iodine-loaded materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Remediation of Temporary Storage Sites in Support of the Port Hope Area Initiative - 20295

The Port Hope Area Initiative is a community-based solution for the long-term management of historic low level radioactive waste (LLRW) resulting from 60 years of uranium and radium processing operations in the Town of Port Hope which is located in Ontario, Canada. The Eldorado refinery, on the north shore of Lake Ontario, began refining radium-226 from pitchblende ore, later transitioning to the refining of uranium. Through the history of the operation, LLRW was deposited throughout the town of Port Hope as a result of fugitive emissions from the plant and/or through the re-use of process residues as building material and backfill. Historical clean-up activities conducted in the late 1970's involved the remediation of approximately 400 properties and the relocation of 100,000 cubic metres of contaminated soil to a disposal facility in Chalk River operated by Atomic Energy of Canada Limited (AECL). Owing to space limitations at that disposal facility, any LLRW identified through construction monitoring since that time has been stored in the community at three temporary storage sites located throughout the town. These include: the Centre Pier mound that contained approximately of 19,800 m{sup 3} of LLRW-impacted soil that originated from the construction of a new water treatment plant; two mounds located at a licensed storage facility containing LLRW obtained from residential clean-up activities (11,000 m{sup 3}); and a small pad adjacent to the municipal sewage treatment plant containing 2200 m{sup 3} of LLRW-containing sludge. With the construction of a new long-term waste management facility (LTWMF) that has been designed to house all of the LLRW identified within Port Hope, the three sites were early candidates for remediation. The clean-up of the three temporary storage sites was a significant milestone for the Port Hope Area Initiative. After a decade of planning and consultation, this work represents the first sites in the municipality to be remediated with the waste being safety removed and transferred to the newly constructed LTWMF. This paper discusses the challenges associated with the clean-up activities for these three sites and the strategies employed to address those challenges. These included weather-related challenges, owing to the seasons over which the work was conducted as well as those associated with working within a closely-knit community. Canadian Nuclear Laboratories (CNL), working on behalf of the federal government, has worked diligently to develop a positive and trusting relationship with the community. Consequently, the successful execution of this project needed to be sensitive to, and respectful of the needs of the community. In addition to the usual Health, Safety and Environment training, project staff received community awareness training that spoke to the history of this community-based initiative and the expected behavior when working within the community. Transportation routes were defined based on safety and the need to minimize disruption to local traffic while haul-times where scheduled around school bus hours to enhance public safety. The successful completion of this first of many remediation projects to be completed under the Port Hope Area Initiative reflected years of careful planning. Nevertheless, there were a number of 'lessons learned' that have been applied on other ongoing projects be completed under the Port Hope Area Initiative. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Structural and antibacterial properties of NSAID-loaded ultra-high molecular weight polyethylene

Peri-articular delivery of pain medication in joint arthroplasty has the potential to address post-operative pain and decrease the use of systemic opioids. Additionally, the sustained release from a delivery vehicle may be especially impactful in the initial post-operative period when pain is most severe. We recently described a novel approach for the sustained intra-articular delivery of an analgesic (bupivacaine) from an ultra-high molecular weight polyethylene (UHMWPE) bearing surface. A secondary but very significant effect of incorporating bupivacaine in UHMWPE was its antibacterial effect against Staphylococcal species, which are associated with the majority of periprosthetic joint infections. Here, we report on the structure, properties, elution characteristics and antibacterial properties of UHMWPE loaded with the non-steroidal anti-inflammatory drug (NSAID) — tolfenamic acid. We showed that 6 wt% drug loading was optimal for eluting clinically relevant intra-articular and systemic concentrations, for maintaining mechanical properties at a clinically relevant level, and for providing anti-colonization potential against low risk (planktonic) and high risk (biofilm forming) Staphylococcal species. We determined the osteoblast response to the tolfenamic acid-loaded UHMWPE to evaluate the cytotoxicity profile of this novel material. Tolfenamic acid-loaded UHMWPE has the potential to be used as a part of multimodal pain management therapy following arthroplasty and may provide prophylaxis for periprosthetic infection.

36 MATERIALS SCIENCE↗

A robust deep learning workflow to predict multiphase flow behavior during geological C O 2 sequestration injection and Post-Injection periods

Simulation of multiphase flow in porous media is essential to manage the geologic CO 2 sequestration (GCS) process, and physics-based simulation approaches usually take prohibitively high computational cost due to the nonlinearity of the coupled physics. This paper contributes to the development and evaluation of a deep learning workflow that accurately and efficiently predicts the temporal-spatial evolution of pressure and CO 2 plumes during injection and post-injection periods of GCS operations. Based on a Fourier Neural Operator, the deep learning workflow takes input variables or features including rock properties, well operational controls and time steps, and predicts the state variables of pressure and CO 2 saturation. To further improve the predictive fidelity, separate deep learning models are trained for CO 2 injection and post-injection periods due to the difference in primary driving force of fluid flow and transport during these two phases. We also explore different combinations of features to predict the state variables. We use a realistic example of CO 2 injection and storage in a 3D heterogeneous saline aquifer, and apply the deep learning workflow that is trained from physics-based simulation data and emulate the physics process. Through this numerical experiment, we demonstrate that using two separate deep learning models to distinguish post-injection from injection period generates the most accurate prediction of pressure, and a single deep learning model of the whole GCS process including the cumulative injection volume of CO 2 as a deep learning feature, leads to the most accurate prediction of CO 2 saturation. For the post-injection period, it is key to use cumulative CO 2 injection volume to inform the deep learning models about the total carbon storage when predicting either pressure or saturation. The deep learning workflow not only provides high predictive fidelity across temporal and spatial scales, but also offers a speedup of 250 times compared to full physics reservoir simulation, and thus will be a significant predictive tool for engineers to manage the long-term process of GCS.

58 GEOSCIENCES↗

Big Hole Drilling Support for Nuclear Testing, 1985-1992: An Architectural Survey of the Area 1 Subdock, Nevada National Security Site, Nye County, Nevada

The U.S. Department of Energy, National Nuclear Security Administration Nevada Field Office (NNSA/NFO) planned to demolish two buildings at the Area 1 Subdock at the Nevada National Security Site (NNSS) in Nye County, Nevada, to meet environmental management mission requirements. A review was conducted under Title 54 United States Code (USC) § 306101 (commonly known as Section 106 of the National Historic Preservation Act) and its implementing regulations, 36 Code of Federal Regulations (CFR) Part 800. As a result, a Memorandum of Agreement (MOA) was developed to mitigate the effects of the building demolitions. Stipulation III.B of the MOA requires an architectural survey of the Area 1 Subdock. Prior to this survey, the Subdock had not been systematically recorded. Therefore, an area of approximately 33 hectares (81 acres) was surveyed for historic properties by Desert Research Institute personnel. This effort resulted in the identification, recording, and evaluation of the potential Area 1 Subdock Historic District (SHPO Resource No. D377), including the identification of its contributing components. This district is recommended as eligible for the National Register of Historic Places (NRHP) under Criteria A and C. It contains 14 primary resources which include individual buildings, structures, storage yards, and infrastructure. Of these resources, all except one are recommended as elements that contribute to the district during its period of significance corresponding to nuclear testing from 1985 through 1992. Four of the resources (B18847, B18848, S2772, S2773) are recommended as individually eligible for the NRHP.

54 ENVIRONMENTAL SCIENCES↗

Update on Activities Related to the Library of Graphite Microstructures

This report provides an overview and update of the ongoing efforts to create a comprehensive library of microstructures for nuclear graphite and carbon-based materials under consideration for nuclear applications. The library includes data on microstructural characterization of unirradiated graphite materials, a guide to the techniques used to analyze graphite (which complements the ASME guidelines and ASTM standards), a summary of characterization data for neutron-irradiated or oxidized material, and a compendium of microstructural information for carbon-based materials. These efforts are being conducted at various length scales for the filler and binder phases in graphite to better understand graphite’s local structure and property relationships. This report is a follow-up to the previous milestone report titled Report on initial development of a database of nuclear graphite characteristics based on microstructural characterization, ORNL/TM/-2023/2992, published in July 2023.The effort to develop the library of microstructures supports the US Department of Energy Office of Advanced Reactor Technologies program objectives of aiding the material selection, licensing, management, and core assessments of a graphite core by documenting the unirradiated microstructure of relevant grades or characterizing the microstructure’s evolution under the reactor environment. Additionally, this project aims to provide (1) information and guidelines for the characterizing of graphite and (2) a protocol to assess a nuclear graphite grade.

36 MATERIALS SCIENCE↗

Assessment of tank designs for hydrogen storage on heavy duty vehicles using metal hydrides

The objective of this project was to evaluate material-based hydrogen storage solutions as a replacement for high-pressure hydrogen gas or liquid hydrogen on Class 7 or 8 tractor fuel cell electric vehicles. The project focused on low-density main-group hydrides, a well-known class of materials for hydrogen storage. Prior research has considered metal amides as storage materials for light-duty vehicles but not for heavy-duty applications. The project established the basis for further development of storage systems of this type for heavy duty vehicles (HDV). Systems analysis of an HDV storage system comprised of a tank and associated balance of plant (piping, coolant tubes, burner) was performed to determine the usable hydrogen capacity. A composite storage material comprised of a metal hydride mixed with a high thermal-conductivity carbon is predicted to have a usable hydrogen volumetric capacity comparable to or exceeding that of 700 bar pressurized hydrogen gas. The gravimetric capacity of this material is also predicted to be competitive with pressurized gas, particularly if costly carbon fiber composite Type III or Type IV tanks are excluded. The storage system design parameters and material properties served as inputs to a second model that simulates fuel cell operation in conjunction with the storage system during an HDV drive cycle. The results show that sufficient hydrogen pressure can be produced to operate a Class 8 HDV, yielding a range of ~480 miles. These results are particularly relevant for high-impact regions, such as the South Coast Air Quality Management District, for which an economical vehicular hydrogen storage system with minimal impact on cargo capacity could accelerate adoption of heavy-duty fuel cell electric vehicles. An additional benefit is that knowledge generated by this project can assist in development of material-based storage for stationary applications such as microgrids and backup power for data centers.

08 HYDROGEN↗

Tailoring thermal insulation architectures from additive manufacturing

Abstract Tailoring thermal transport by structural parameters could result in mechanically fragile and brittle networks. An indispensable goal is to design hierarchical architecture materials that combine thermal and mechanical properties in a continuous and cohesive network. A promising strategy to create such a hierarchical network targets additive manufacturing of hybrid porous voxels at nanoscale. Here we describe the convergence of agile additive manufacturing of porous hybrid voxels to tailor hierarchically and mechanically tunable objects. In one strategy, the uniformly distributed porous silica voxels, which form the basis for the control of thermal transport, are non-covalently interfaced with polymeric networks, yielding hierarchic super-elastic architectures with thermal insulation properties. Another additive strategy for achieving mechanical strength involves the versatile orthogonal surface hybridization of porous silica voxels retains its low thermal conductivity of 19.1 mW m −1 K −1 , flexible compressive recovery strain (85%), and tailored mechanical strength from 71.6 kPa to 1.5 MPa. The printed lightweight high-fidelity objects promise thermal aging mitigation for lithium-ion batteries, providing a thermal management pathway using 3D printed silica objects.

36 MATERIALS SCIENCE↗

Design of solvent-assisted plastics recycling: Integrated economics and environmental impacts analysis

In 2018, the United States generated over 35. 7 million tons of plastic waste, with only 8.4% being recycled and the other 91.6% incinerated or disposed of in a landfill. The continued growth of the polymer market has raised concerns over the end of life of plastics. Currently, the waste management system is faced with issues of inefficient sorting methods and low-efficiency recycling methods when it comes to plastics recycling. Mechanical recycling is the commonest recycling method but presents a lower-valued recycled material due to the material incompatibilities introduced via the inefficient sorting methods. Chemical recycling offers a promising alternative as it potentially allows for plastics to maintain their original properties. To that end, there is the need to investigate feasible chemical recycling methods to help mitigate the challenging problem posed by plastics at the end-of-life stage. This work proposes a conceptual solvent-assisted plastics recycling framework based on a superstructure optimization approach. This framework is evaluated using a representative case study to recover Polyethylene Terephthalate (PET). In this case study, it is found that polymer recovery is both economically and environmentally favorable when compared to traditional methods of disposal such as incineration.

Lehr, Austin L.↗

Physical and Flow Properties of Glass-Forming Chemicals (V 2 O 5 , SnO, SnO 2 , Cr 2 O 3 , FeCr 2 O 4 , and ZrSiO 4 ) and Mixtures

For an efficient nuclear waste vitrification process at the Waste Treatment and Immobilization Plant (WTP) on the Hanford Site, proper selection and consistent supply of glass-forming chemicals (GFCs) are crucial. Thorough characterization of the GFCs is required to reduce risks in operation of the vitrification facility. Low-activity waste (LAW) will be blended with GFCs to form slurry feeds and then fed to melters and vitrified. To enhance properties of waste glasses, new chemicals are being introduced to the current GFC mixture. In this study, three new GFCs were evaluated for enhanced LAW glass formulations: chromium oxide (Cr 2 O 3 ), vanadium oxide (V 2 O 5 ), and stannic oxide (SnO 2 ). These three oxide components are included in enhanced waste glass formulations, and GFCs with the appropriate physical and flow properties are needed. As a starting point, single metal oxide GFCs, Cr 2 O 3 , V 2 O 5 , and SnO 2 , were sourced and tested. Then, alternative sources of Sn and Cr (SnO and FeCr 2 O 4 ) were tested along with an alternative zircon source (ZrSiO 4 ). This report documents the work performed to collect physical and flow property data on these new GFCs and melter feed slurries generated using these GFCs and simulated low-activity wastes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Divergent accumulation of amino sugars and lignins mediated by soil functional carbon pools under tropical forest conversion

Tropical primary forests are being destroyed at an alarming rate and converted for other land uses which is expected to greatly influence soil carbon (C) cycling. However, our understanding of how tropical forest conversions affect the accumulation of compounds in soil functional C pools remains unclear. Here, we collected soils from primary forests (PF), secondary forests (SF), oil-palm (OP), and rubber plantations (RP), and assessed the accumulation of plant- and microbial-derived compounds within soil organic carbon (SOC), particulate (POC) and mineral-associated (MAOC) organic C. PF conversion to RP greatly decreased SOC, POC, and MAOC concentrations, whereas conversion to SF increased POC concentrations and decreased MAOC concentrations, and conversion to OP only increased POC concentrations. PF conversion to RP decreased lignin concentrations and increased amino sugar concentrations in SOC pools which increased the stability of SOC, whereas conversion to SF only increased the lignin concentrations in POC, and conversion to OP just increased lignin concentrations in POC and decreased it in MAOC. We observed divergent dynamics of amino sugars (decrease) and lignin (increase) in SOC with increasing SOC. Only lignin concentrations increased in POC with increasing POC and amino sugars concentrations decreased in MAOC with increasing MAOC. Conversion to RP significantly decreased soil enzyme activities and microbial biomasses. Lignin accumulation was associated with microbial properties, whereas amino sugar accumulation was mainly associated with soil nutrients and stoichiometries. These results suggest that the divergent accumulation of plant- and microbial-derived C in SOC was delivered by the distribution and original composition of functional C pools under forest conversions. Forest conversions changed the formation and stabilization processes of SOC in the long run which was associated with converted plantations and management. As a result, the important roles of soil nutrients and stoichiometry also provide a natural-based solution to enhance SOC sequestration via nutrient management in tropical forests.

59 BASIC BIOLOGICAL SCIENCES↗

Parametric reduced order models for graded lattice structures

Graded lattice structures, characterized by smoothly varying mechanical properties, hold significant promise for optimizing material distribution in advanced engineering applications. However, accurately modeling these structures poses substantial computational challenges due to the continuous geometric variations within their unit cells. Here, to address these challenges, this paper introduces a novel Efficient Reduced Order Model (EROM) that integrates the Matrix Discrete Empirical Interpolation Method (MDEIM) and Discrete Empirical Interpolation Method (DEIM) with polynomial regression to efficiently manage geometric parametrization in lattice structures. Unlike traditional reduced order models (ROMs) that require extensive precomputed libraries for each geometric configuration, our approach enables continuous geometric variations through a flexible algebraic formulation, significantly reducing computational costs while preserving high accuracy. The method constructs projection matrices for individual unit cells that can be efficiently assembled into global systems, leveraging the repetitive nature of lattice structures. Numerical studies demonstrate that our EROM achieves displacement errors below 1% and von Mises stress prediction errors below 4%, coupled with computational speedups exceeding two orders of magnitude compared to full-order simulations. The proposed method's modularity and scalability make it particularly suitable for design optimization and real-time simulation of functionally graded lattice structures, with applications spanning aerospace to biomedical engineering.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗