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At least 73 records · Page 4

Reactor assemblies and methods of performing reactions

Reactors are provided that can include a first set of fluid channels and a second set of fluid channels oriented in thermal contact with the first set of fluid channels. The reactor assemblies can also provide where the channels of either one or both of the first of the set of fluid channels are non-linear. Other implementations provide for at least one of the first set of fluid channels being in thermal contact with a plurality of other channels of the second set of fluid channels. Reactor assemblies are also provided that can include a first set of fluid channels defining at least one non-linear channel having a positive function, and a second set of fluid channels defining at least another non-linear channel having a negative function in relation to the positive function of the one non-linear channel of the first set of fluid channels. Processes for distributing energy across a reactor are provided. The processes can include transporting reactants via a first set of fluid channels to a second set of fluid channels, and thermally engaging at least one of the first set of fluid channels with at least two of the second set of fluid channels.

Zheng, Richard F.↗

Distributionally Robust Partially Observable Markov Decision Process with Moment-Based Ambiguity

In this paper, we consider a distributionally robust partially observable Markov decision process (DR-POMDP), where the distribution of the transition-observation probabilities is unknown at the beginning of each decision period, but their realizations can be inferred using side information at the end of each period after an action being taken. We build an ambiguity set of the joint distribution using bounded moments via conic constraints and seek an optimal policy to maximize the worst-case (minimum) reward for any distribution in the set. We show that the value function of DR-POMDP is piecewise linear convex with respect to the belief state and propose a heuristic search value iteration method for obtaining lower and upper bounds of the value function. We conduct numerical studies and demonstrate the computational performance of our approach via testing instances of a dynamic epidemic control problem. Our results show that DR-POMDP can produce more robust policies under misspecified distributions of transition-observation probabilities as compared to POMDP but has less costly solutions than robust POMDP. The DR-POMDP policies are also insensitive to varying parameter in the ambiguity set and to noise added to the true transition-observation probability values obtained at the end of each decision period.

97 MATHEMATICS AND COMPUTING↗

Data transfer for STAR grid jobs

The Solenoidal Tracker at RHIC (STAR) is a multipurpose experiment at the Relativistic Heavy Ion Collider (RHIC) with the primary goal to study the formation and properties of the quark-gluon plasma. STAR is an international collaboration of member institutions and laboratories from around the world. Yearly data-taking period produces PBytes of raw data collected by the experiment. STAR primarily uses its dedicated facility at BNL to process this data, but has routinely leveraged distributed systems, both high throughput (HTC) and high performance (HPC) computing clusters, to significantly augment the processing capacity available to the experiment. The ability to automate the efficient transfer of large data sets on reliable, scalable, and secure infrastructure is critical for any large-scale distributed processing campaign. For more than a decade, STAR computing has relied upon GridFTP with its x509-based authentication to build such data transfer systems and integrate them into its larger production workflow. The end of support by the community for both GridFTP and the x509 standard requires STAR to investigate other approaches to meet its distributed processing needs. In this study we investigate two multi-purpose data distribution systems, Globus.org and XRootD, as alternatives to GridFTP. We compare both their performance and the ease by which each service is integrated into the type of secure and automated data transfer systems STAR has previously built using GridFTP. The presented approach and study may be applicable to other distributed data processing use cases beyond STAR.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Evolution of DUNE’s Production System

The DUNE experiment will start running in 2029 and record 30 PB/year of raw waveforms from Liquid Argon TPCs and photon detectors. The size of individual readouts can range from 100 MB to a typical 8 GB full readout of the detector, and even 100 TB for extended readouts from supernova candidates. These data then need to be cataloged, stored and distributed for processing worldwide. This massive amount of data and a heterogeneous computing environment necessitates a powerful and robust distributed computing infrastructure. In the process of building up that infrastructure, DUNE’s production system has recently undergone an overhaul, in which it has integrated 1) a new workflow management system (justIN) 2) a new data catalog (MetaCat) and 3) a state-of-the-art data management system (Rucio). Simulations of DUNE’s Far Detector and its prototypes ProtoDUNE Horizontal Drift (ProtoDUNE-HD) and ProtoDUNE Vertical Drift (ProtoDUNE-VD), as well as data from ProtoDUNE-HD serve as the first tests of this infrastructure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Restoring Historic Forest Disturbance Frequency Would Partially Mitigate Droughts in the Central Sierra Nevada Mountains

Forest thinning and prescribed fire are expected to improve the climate resilience and water security of forests in the western U.S., but few studies have directly modeled the hydrological effects of multi-decadal landscape-scale forest disturbance. By updating a distributed process-based hydrological model (DHSVM) with vegetation maps from a distributed forest ecosystem model (LANDIS-II), we simulate the water resource impacts of forest management scenarios targeting partial or full restoration of the pre-colonial disturbance return interval in the central Sierra Nevada mountains. In a fully restored disturbance regime that includes fire, thinning, and insect mortality, reservoir inflow increases by 4%–9% total and 8%–14% in dry years. At sub-watershed scales (10–100 km2), thinning dense forests can increase streamflow by >20% in dry years. In a thinner forest, increased understory transpiration compensates for decreased overstory transpiration. Consequentially, 73% of streamflow gains are attributable to decreased overstory rain and snow interception loss. Thinner forests can increase headwater peak flows, but reservoir-scale peak flows are almost exclusively influenced by climate. Uncertainty in future precipitation causes high uncertainty in future water yield, but the additional water yield attributable to forest disturbance is about five times less sensitive to annual precipitation uncertainty. This partial decoupling of the streamflow disturbance response from annual precipitation makes disturbance especially valuable for water supply during dry years. Our study can increase confidence in the water resource benefits of restoring historic forest disturbance frequencies in the central Sierra Nevada mountains, and our modeling framework is widely applicable to other forested mountain landscapes.

Boardman, Eli N. [University of Nevada, Reno, NV (↗

Opportunities for Integrating Electric and Gas Planning

Growing demand for electricity in buildings is creating new opportunities and challenges for electric and natural gas planning. To date, electric and gas planning processes have largely been siloed, and only a few jurisdictions have started to examine how these two processes could be linked together. The report explores the current state of electric and gas system planning, and the benefits and challenges of integrating these planning processes. We frame the characteristics of an integrated electric and gas distribution planning process and identify indicators of progress toward the characteristics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Catalyzing deep decarbonization with federated battery diagnosis and prognosis for better data management in energy storage systems

Industrial data analytics methods play a central role in improving energy storage performance and efficiency, impacting the future of electrified transportation and renewable electricity generation. However, significant challenges hinder the large-scale deployment of batteries. Conventional methods rely on centralized collection and processing of fleet-level data, leading to database size issues and privacy concerns due to potential data breaches. To enable scalable deployment of battery management systems, this article proposes a federated battery diagnosis and prognosis model, which distributes the processing of battery standard current-voltage-time-usage data in a privacy-preserving manner. Instead of transferring the raw data, this approach communicates only the locally processed parameters, thus reducing communication load and preserving data confidentiality. The federated model offers a paradigm shift in battery health management through privacy-preserving distributed methods for battery data processing and lifetime prediction, ensuring the reliable and sustainable deployment of lithium-ion batteries in a rapidly evolving world.

asset health management↗

Switching Device-Cognizant Sequential Distribution System Restoration

This paper presents an optimization framework for sequential reconfiguration using an assortment of switching devices and repair process in distribution system restoration. Compared to existing studies, this paper considers types, capabilities and operational limits of different switching devices, making it applicable in practice. We develop a novel multi-phase method to find the optimal sequential operation of various switching devices and repair faulted areas. We consider circuit breakers, reclosers, sectionalizers, load breaker switches, and fuses. The switching operation problem is decomposed into two mixed-integer linear programming (MILP) subproblems. The first subproblem determines the optimal network topology and estimates the number of steps to reach that topology, while the second subproblem generates a sequence of switching operations to coordinate the switches. For repairing the faults, we design an MILP model that dispatches repair crews to clear faults and replace melted fuses. After clearing a fault, we update the topology of the network by generating a new sequence of switching operations, and the process continues until all faults are cleared. To improve the computational efficiency, a network reduction algorithm is developed to group line sections, such that only switchable sections are present in the reduced network. The proposed method is validated on the IEEE 123-bus and 8500-bus systems.

distribution system↗

Distribution Development for the RDX Regional Model at Los Alamos National Laboratory - 20385

Representing uncertainty in model inputs often means finding a balance between uncertainty and physical reality. Developing wide distributions may seem conservative in principle, but this approach may lead to unrealistic model results. Characterizing the current state of knowledge of stochastic inputs presents many challenges, especially if the data available are limited or have limited relevance to the site. Relationships among these inputs may also be important to represent but are typically complex or difficult to define. Often special adjustments must be made to account for reduced credibility in particular data. If parameters are strongly related to one another, a correlation structure may be developed for input to the model. Other techniques such as regression models may be used to incorporate relationships between the information available and the desired parameters. The process of developing distributions must consider details of the model in terms of what the distribution is meant to represent. This paper uses the example of a probabilistic fate and transport model for hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) in the regional aquifer at Los Alamos National Laboratory (LANL). For many parameters, a single draw is applied to all space and time over which the model is run, for a single iteration. This simplification is often made for many reasons, and can often be beneficial, but also adds additional complexity in the distribution development process. Defining the distributional goals as they relate to the modeling process is an important step, which should take place prior to evaluation of the data. Usually, the distributions developed are meant to characterize the average value of the parameter over the spatial and temporal domain of the model. Distribution development requires consideration of many sources of information on the parameter where available, ideally from multiple references. Examples of different sources include data from different references but also from different conditions, measurement methods, or experimental types. Depending on these conditions and the reliability or relevance of particular references, different sources of data may each contribute valuable information but have varying relevance to the site. In these cases, weighting data unequally is a useful way to incorporate this information. As an example, aqueous dispersivity data are available for a variety of rock types. Only a few values are available for the desired rock type, and this is not enough to develop a distribution. Therefore, dispersivity values from other rock types are included in distribution development but are down-weighted such that the best data have the most influence on the distribution developed. In another case, K{sub d} distributions in the model are meant to represent a known composition of multiple soil types. Data from these materials are weighted accordingly to develop a distribution for the weighted average K{sub d} across soil types. Other cases include varying reliability of different sources, and weighting data according to the confidence in these sources. In some cases, input parameters are correlated with one another. An example is advective porosity, which is positively correlated with total porosity and must be less than total porosity. Paired data with both parameters must exist to discern the relationship between the two parameters and if it is necessary to build a correlation structure into the model. In general, correlated parameters may be represented in the model by a multivariate distribution, or perhaps more desirably, capturing the correlation within the developed distributions which may be treated as independent from one another. In the example of porosity, this can be done by transforming advective porosity into a proportion of total porosity which may be drawn independently from the distribution of total porosity. This paper explores how complex data and correlations can be incorporated to meet the distributional goals of the model, using the RDX regional model as a detailed example. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Microhardness Distribution of Long Magnesium Block Processed through Powder Metallurgy

Powder metallurgy is a popular method of making raw powders into specific shaped samples. However, the pressure distribution and the microhardness difference within the sample are nonnegligible and unclear when the sample is long or exceeds a specific size. In this study, the long magnesium blocks, with a ratio of about 2.8 between the sample height and the sample side length, are successfully synthesized under three uniaxial and two biaxial conditions. Then, the sample hardness values on the outer surface and the center plane are tested to study the microhardness distribution. The modified analytical expression indicates that the normal pressure exponentially decreases along the compression direction, which is consistent with the hardness distribution trend. Because higher pressure leads to a more compact arrangement of the powders, more metal bonds are formed after sintering. During the first pressing, the sidewall pressure makes the surface hardness higher. The secondary reverse compression mainly improves the bottom and core hardness due to the re-orientation and re-location of the powders. The obtained relationship between the applied pressure and the hardness distribution is instructive in predicting and improving the sample quality.

Wang, Jiaying↗

Cost and Efficiency Analysis for Hybrid AC/DC Distribution System Planning with PV and Battery

Distribution system planning is one of the main tasks for the electric utilities. Cost and energy efficiency are two main concerns in the distribution planning process. In this work, cost and efficiency analyses are conducted for the hybrid AC and DC distribution grids for the planning purposes. The IEEE 34-bus feeder has been applied for the case studies. The investment cost, operation and maintenance cost, replacement cost, etc., have been considered in the life cycle cost analysis. Power losses of both the AC and DC section are calculated with an open source simulation tool, the Open Distribution Simulator Software (OpenDSS). The proposed framework can be applied to quantitatively evaluate the cost and efficiency of hybrid AC and DC distribution grids and help comparing different planning options.

AC/DC hybrid system planning↗

SolarAPP+ Enhancements and Commercialization (Final Technical Report)

With millions of distributed photovoltaic (PV) systems expected to be installed over the next five years, the permitting and inspection processes of authorities having jurisdiction (AHJs) may become overburdened, causing delays and increased costs for installed systems (Cruce et al. 2022). The central goal of this project was to automate and streamline permitting processes for distributed PV systems and complementary technologies, such as battery storage. Deploying automated permitting has been hypothesized to reduce permit review times, resulting in reduced costs and improved customer experience. This has the potential to expand the PV and PV-plus-storage market nationwide. The National Renewable Energy Laboratory (NREL) and its project partners, including UL Solutions, the Interstate Renewable Energy Council (IREC), the International Code Council (ICC), and more, developed the Solar Automated Permit Processing (SolarAPP+™) software platform to reduce permit review times. NREL and its partners also collaborated with the solar industry, the building safety community, and local governments to develop SolarAPP+.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Thermal aging effects on crosslinked polyethylene cable insulation with decabromodiphenyl ether flame retardant alternative

Decabromodiphenyl ether (decaBDE) has been extensively used as a flame retardant in several applications, including nuclear electrical cable insulation. However, decaBDE has been identified as a persistent, bioaccumulative and toxic (PBT) substance, leading to regulatory scrutiny. The Environmental Protection Agency (EPA) published a regulation on January 6, 2021, aimed at phasing out the manufacturing, processing, and distribution of decaBDE. This rule set a compliance deadline of March 8, 2021, for the manufacture and processing of decaBDE, and an extended deadline of January 6, 2023, for specific applications including wire and cable insulation in nuclear power generation facilities. In response to such regulations, RSCC, a major supplier of safety-related electrical cables and associated products to the U.S. nuclear industry updated the formula of their crosslinked polyethylene (XLPE) insulation to replace the historically used decaBDE flame retardant with an acceptable alternative. This change from the previous decaBDE-containing XLPE prompted interest in comparative performance of the two material formulations, especially with respect to characteristics relevant to safety-related function such as thermal and radiation resistance. RSCC graciously provided samples of wire insulated with the decaBDE-containing XLPE formulation and corresponding wire insulated with XLPE of the new formulation, containing a decaBDE alternative. In this work we compare characteristics of the two formulations and a previously produced commercial version of the RSCC decaBDE-containing XLPE insulation subjected to thermal aging at 150 °C and 165 °C. The comparison was focused on mechanical durability, thermal stability in the oxidative environment, and chemical structures. Briefly, • Tensile elongation at break (EAB) results showed loss of mechanical elasticity with longer aging time, as expected. Aging time dependence of EAB did not differ between the decaBDE-containing and decaBDE-alternative samples. • Subtle differences between the two materials can be detected from Fourier-transform infrared spectroscopy (FTIR) absorbance spectra in the range below 1700 cm -1 , are assumed to be related to decomposition of flame retardant additives during thermal aging. • The oxidation induction time (OIT) data seemed to show that the unaged decaBDE-containing XLPE material is more thermally stable than the unaged decaBDE-alternative material, but the discrepancy in OIT decreased with aging time and the OIT values of the two materials became similar starting with the 4 th day of aging at 165 °C. This thermal aging investigation confirmed that the mechanical durability, a key property monitored for cable qualification, was not significantly affected by the modification of the formulation with a decaBDE alternative flame-retardant system in the investigated thermal aging conditions. Further studies on the same sets of materials exposed to thermal and gamma radiation aging would further inform comparison of the materials safety-related function.

36 MATERIALS SCIENCE↗

Distributed Ledger Technology for Fault Tolerant Distribution Grid Operations

This paper explores the potential of distributed ledger technology (DLT) to improve fault-tolerant grid operations by leveraging its core features as an immutable, decentralized ledger, a distributed, consensus-based agreement process, and a distributed state-replication engine. Distribution power systems deliver electricity to millions of customers; however, they are susceptible to various threats that can result in customer interruptions. These include faults caused by adverse weather conditions, natural disasters, vegetation growth, equipment failure, and malicious attacks. To minimize the effects of these faults, fault-handling approaches rely on network knowledge to isolate affected areas and reconnect unaffected areas, reducing the number of affected customers while maintaining safety. Here, we present a trusted data-sharing architecture that enables independent, distributed actors to reconstruct the pre-fault system state by enabling distributed resources to make appropriate decisions with limited network/system information. Although the process requires some data sharing between switch-delimited areas, the approach limits the amount of private information shared, preserving customers' privacy and business-sensitive information. We include three use cases that form a foundation for third parties to develop functional solutions that can eventually be deployed in the field. The gross error detection method used within switch-delimited areas can identify sensor errors and accurately detect circuit breaker states. The evaluation of possible reconnection while preserving data ownership resulted in a voltage magnitude difference smaller than 0.001% from the OpenDSS power flow solution that has full system knowledge, which is below the expected power flow tolerance. The approach offers a promising opportunity for improving fault-tolerant distribution grid operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

SAN-Based Block Polymers as a Platform for Manufacturing Strong Isoporous Membranes

Ultrafiltration (UF) membranes are ubiquitous in water purification and bioprocessing. However, co-designing their mechanical and transport properties remains challenging because of the broad pore size distributions at the surface and within the bulk that result from nonsolvent-induced phase separation (NIPS) – their typical manufacturing process. These distributions influence the hydrodynamic resistance to water flow and the stress concentrations around the pores. Developing advanced UF membranes requires innovative molecular designs that offer control over the surface and bulk pores, as well as the mechanical properties of the load-bearing, polymer. Here, we introduce a platform for designing UF membranes by leveraging solution self-assembly of block polymers and chain architectures with pendant polar groups. The block polymers consist of a poly(styrene-co-acrylonitrile) hydrophobic block, which is known for its strength, and a poly(4-vinyl pyridine) hydrophilic block, which drives solution self-assembly. We focus on a series of block polymers with constant molecular weight, M n ≈ 115 kDa, SAN fraction, 75 wt.%, and varying acrylonitrile content, 0 to 40 mol%, to demonstrate that: (i) RAFT dispersion copolymerization of acrylonitrile and styrene provides a facile route to synthesize strong block polymers, (ii) incorporation of acrylonitrile into the hydrophobic block enhances membrane strength by facilitating chain entanglements and dipole-dipole interactions, and (iii) acrylonitrile alters the balance between membrane permeance and rejection, even when the membranes feature similar surface and bulk pores. Overall, our results provide insights into the molecular design of UF membranes with enhanced mechanical and separation properties, contributing to the development of materials for water and energy technologies.

deformation↗

High Performance Computing to Quantify the Evolution of Microscopic Concentration Gradients During Flash Processing

During the Flash process, the cross section of a plain-carbon or a low-alloy steel is austenitized through rapid heating and transformed on rapid cooling to a predominantly martensite + bainite structure with small amounts of retained austenite. Unlike conventional heat treating, homogeneity is intentionally avoided during Flash processing of steels. The Flash process assembly consists of a pair of rolls that transfer the steel sheets through the heating and cooling stage of the thermal cycle. The initial microstructure of the steel consists of ferrite (body-centered cubic iron) + carbide ((Fe,X)mCn) mixture. The heating rate through the peak temperature is a function of temperature and reaches a peak of about 300-400°C/s and the cooling rate has a maximum value of 3,000-4,000°C/s. The on-heating phase transformations include carbide dissolution, austenite (face-centered cubic iron) nucleation and growth, and diffusion of carbon and other substitutional elements in the steel. The on-cooling phase transformations include formation of martensite (body-centered tetragonal phase containing supersaturated solute) and bainite (ferrite plates with or without fine carbides). In this project, the focus is on Fe-C-Cr steels that are currently Flash processed for armor applications. The modeling effort proposed here will help optimize the Flash thermal cycle for these low alloy steels to achieve the target performance, which is an ongoing effort at SFP Works. A significant feature of Flash processed Fe-C-Cr steels is the presence of scatter in the through-thickness in the sheet. The variability in hardness results from a variability in the bainite + martensite microstructure that is sensitive to the local chemical concentration of C and Cr. Such a chemical inhomogeneity is intentionally obtained in the Flash process. Although such a microstructural gradient is presumably responsible for the exceptional properties of the Flash processed steel, it is very important to quantify the gradients as a function of Flash variabilities in processing parameters and the input microstructure. Understanding the mechanistic pathway that leads to microstructural gradients could be ground-breaking and instrumental for achieving better process control and optimized microstructural state to meet application-specific strength-ductility requirements. Since the final microstructure depends on setting up precise solute concentration gradients through a rapid heating process, and transforming these regions into various phases, it is important to understand how small changes in steel chemistry, input microstructure (carbide size and distribution), and process variables (Flash thermal cycle) will impact the solute concentration gradients.

97 MATHEMATICS AND COMPUTING↗