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DOE OSTI2022

Investigating uncertainties in human adaptation and their impacts on water scarcity in the Colorado river Basin, United States

The Colorado River Basin (CRB) supports the water supply for seven states and forty million people in the Western United States (US) and has been suffering an extensive drought for more than two decades. As climate change continues to reshape water resources distribution in the CRB, its impact can differ in intensity and location, resulting in variations in human adaptation behaviors. The feedback from human systems in response to the environmental changes and the associated uncertainty is critical to water resources management, especially for water-stressed basins. This paper investigates how human adaptation affects water scarcity uncertainty in the CRB and highlights the uncertainties in human behavior modeling. Our focus is on agricultural water consumption, as approximately 80% of the water consumption in the CRB is used in agriculture. We adopted a coupled agent-based and water resources modeling approach for exploring human-water system dynamics, in which an agent is a human behavior model that simulates a farmer’s water consumption decisions. We examined uncertainties at the system, agent, and parameter levels through uncertainty, clustering, and sensitivity analyses. The uncertainty analysis results suggest that the CRB water system may experience 13 to 30 years of water shortage during the 2019–2060 simulation period, depending on the paths of farmers’ adaptation. The clustering analysis identified three decision-making classes: bold, prudent, and forward-looking, and quantified the probabilities of an agent belonging to each class. The sensitivity analysis results indicated agents whose decision-making models require further investigation and the parameters with the higher uncertainty reduction potentials. Here, by conducting numerical experiments with the coupled model, this paper presents quantitative and qualitative information about farmers’ adaptation, water scarcity uncertainties, and future research directions for improving human behavior modeling.

Agent-based modeling↗

DOE OSTI2013

Fabrication of platinum nanoparticles in aqueous solution and solid phase using amphiphilic PB-b-PEO copolymer nanoreactors

Graphical abstract: TEM image of Pt nanoparticles produced by reducing by NaBH{sub 4} within PB-b-PEO micelles in aqueous media (scale bar 1 nm). - Highlights: • Pt nanoparticles were synthesized within amphiphilic diblock copolymer micelles. • The effects of reducing agents and precursor dose on Pt np size were investigated. • The effect on fabrication of Pt np by reducing in aqueous and solid phases was compared. • The size of nanoparticles was about 1.4 nm for all doses and reducing agents types. - Abstract: Fabrication of Pt nanoparticles using an amphiphilic copolymer template in aqueous solution was achieved via polybutadiene-block-polyethyleneoxide copolymer micelles, which acted as nanoreactors. In addition, Pt nanoparticles were synthesized using hydrogen gas as the reducing agent in solid state for the first time to compare against solution synthesis. The influences of loaded precursor salt amount to micelles and the type of reducing agent on the size of nanoparticles were investigated through transmission electron microscopy. It was found that increasing the ratio of precursor salt to copolymer and using different type of reducing agent, even in solid phase reduction, did not affect the nanoparticle size. The average size of Pt nanoparticles was estimated to be 1.4 ± 0.1 nm. The reason for getting same sized nanoparticles was discussed in the light of nucleation, growth process, stabilization and diffusion of nanoparticles within micelles.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Resilient Distributed Parameter Estimation With Heterogeneous Data

This paper studies resilient distributed estimation under measurement attacks. A set of agents each makes successive local, linear, noisy measurements of an unknown vector field collected in a vector parameter. The local measurement models are heterogeneous across agents and may be locally unobservable for the unknown parameter. An adversary compromises some of the measurement streams and changes their values arbitrarily. The agents' goal is to cooperate over a peer-to-peer communication network to process their (possibly compromised) local measurements and estimate the value of the unknown vector parameter. We present SAGE, the Saturating Adaptive Gain Estimator, a distributed, recursive, consensus + innovations estimator that is resilient to measurement attacks. We demonstrate that, as long as the number of compromised measurement streams is below a particular bound, then, SAGE guarantees that all of the agents' local estimates converge almost surely to the value of the parameter. The resilience of the estimator - i.e., the number of compromised measurement streams it can tolerate - does not depend on the topology of the inter-agent communication network. Finally, we illustrate the performance of SAGE through numerical examples.

42 ENGINEERING↗

NASA NTRSDate not supplied

APIS: Honeybee Foraging Task Assignment for Use in Uncertain and Unreliable Environments

Multiagent Cyber-Physical-Human (CPH) systems in realistic environments operate under uncertain conditions. Communication among agents, aimed at reducing the uncertainty, is itself subject to uncertainty. We propose to manage uncertainties in autonomous, long-duration operations of multiagent systems via a modified Honeybee Foraging (HBF) behavioral scheme. The resulting system, Autonomous Persistent Intelligent Swarm (APIS),incorporates two new behaviors to ameliorate informational uncertainty. When “scouting”, agents are tasked based on informational quality and reliability rather than solely on priorities. When “dancing”, agents are tasked to rendezvous with other dancing agents to exchange information at close range, where successful communication is guaranteed. When coupled with uncertainty-aware modeling across agents, these behaviors improve situational awareness and resilience of the system, enabling it to function under more uncertain conditions arising during long-duration missions.

Autonomous systems↗

NASA NTRSDate not supplied

APIS: Honeybee Foraging Task Assignment for Use in Uncertain and Unreliable Environments

Autonomous systems↗

DOE OSTI2016

Evaluation of TiO{sub 2} and TiO{sub 2}/Au nanoparticles as a Potential Radiosensitizers by Decomposition of Methylene Blue

Nanomaterials are constantly used in several applications of science and engineering. Nanoparticles are currently utilized in computer circuits, clothes, luminescent devices, catalysis, medicine, among many others uses. In the clinical field nanomaterials have become an innovative alternative for early diagnosis and treatment of a significant number of medical conditions. Nanoparticles can be utilized in applications ranging from contrast agents for imaging purposes to carriers for drug delivery in cancerous tumors. The use of nanoparticles made of high atomic number elements as noble metals, is becoming an attractive approach for enhancing the radiation dose delivered to a tissue during radiation therapy. The enhancement effect that makes the cells more sensitive to radiation is known as radiosensitization. Materials such as gold (Au) and titanium dioxide (TiO{sub 2}) at the nanoscale have become promising radiosensitizers. When TiO{sub 2} is irradiated with high energy photons, electron-holes are created within the material. This species interacts with surrounding medium generating reactive oxygen species (ROS). ROS create a toxic environment for cancerous cells, ultimately causing their death. On the other hand gold has a different interaction with ionizing radiation. Upon radiation, gold releases a spray of secondary products such as photoelectrons, auger electrons, and characteristic X-rays. The energy created by the escaping electrons leads to DNA strands breaks in the cells causing their death. Therefore, if these nanoparticles are initially accumulated in the tissue to be treated, the dose delivered during radiation therapy is amplified. This represents a synergistic approach to enhance radiation therapy while substantially reducing side effects. Radiosensitization by nanoparticles often depends on their particle size, morphology and synthesis route. The most commonly used methods to synthesize metallic nanoparticles such as gold involves chemical reduction of a metal precursor. In this case, reducing agents are used in order to transform the metallic ions to metal atoms that will subsequently coalesce and grow to form the nanoparticles . Nevertheless there are alternative methods that do not require a chemical reducing agent. Radiation synthesis is one of those processes. The interaction of ionizing radiation with an aqueous solution containing a metal precursor, leads to a phenomena known as radiolysis of water. Radiolysis of water produces chemical species such as solvated electrons (e{sup -}{sub aq}), and hydrogen atoms (H{sup +}). These species are strong reducing agents that bring the metal ions existing in solution into stable metal atoms that will form nanoparticles. Radiation synthesis is a novel method that offers significant advantages over conventional approaches such as wet chemistry routes. In this approach, no further chemical reducing agents are needed, thus it does not generate byproducts that may affect the nanoparticles properties. This is particularly important in medical applications. Furthermore, this technique is designed to work at room temperature and under atmospheric pressures. Nonetheless the most outstanding feature of radiation synthesis is the possibility to control the particle size and size distribution. This route allows for narrow particle size distributions with size ranging from 2 to 30 nm. Furthermore, the availability of different ionizing radiation producing devices such as synchrotrons, X-ray irradiators, and gamma irradiators enables the possibility of manufacturing nanomaterials under various conditions. In this work, Au nanoparticles were deposited onto TiO{sub 2} using the radiation synthesis method. In addition, the radiosensitization characteristics of TiO{sub 2} and TiO{sub 2}/Au nanoparticles were evaluated through the decomposition of the organic dye Methylene Blue (MB). In order to analyze the degradation of the dye the TiO{sub 2} and TiO{sub 2}/Au nanoparticles were placed in an aqueous solution along with MB and subjected to X-ray irradiation. The samples were irradiated for 30 and 60 minutes. The degradation of the MB after irradiation in the presence and absence of the nanomaterials was measured by UV-Vis spectroscopy following the decrease in the absorbance of the dye at 664 nm. (authors)

36 MATERIALS SCIENCE↗

DOE OSTI2014

Molecular Sensing Using Hyperpolarized Xenon NMR Spectroscopy

Molecular imaging is defined as the determination of the spatial location and concentration of specific molecules in a sample of interest. Sophisticated modern magnetic resonance imaging machines can collect NMR spectra from small-volume elements within a sample, enabling local chemical analysis. However, abundant water and fat signals limit detection of metabolites to near mm concentrations. Alternatively, targeted relaxation contrast agents enhance the relaxation of the strong water signal where they bind. A comparison of images with and without a contrast agent shows the target distribution, but high mm concentrations are needed. We have developed an approach that exploits the strong signals of hyperpolarized 129 Xe (an inert reporter introduced for imaging). The imaging contrast agents are composed of a biological recognition motif to localize the agent (antibodies or aptamers) and covalently tethered cryptophane cages. Xenon binds to the cryptophane and though chemical exchange saturation transfer creates contrast in a xenon image. Imaging agents can deliver many cages per target, giving detection limits in the pm concentration range. The evolution and principles of this approach are described.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Quinoa protein extract: an effective alternative for the fining of wine phenolics

Abstract BACKGROUND Lately, there has been an increasing interest in using plant‐derived proteins for wine phenolic fining. Proteins extracted from cereals, potatoes, and legumes have been proposed as effective fining agents, but only those from pea, wheat, and potatoes have been approved for their use in wine. This work aimed at determining the fining ability of quinoa ( Chenopodium quinoa Willd.) protein extracts (QP), compared to commercial fining agents, on red wines. RESULTS The trials compared the performance of QP (30 and 50 g/hL), two potato protein extracts and gelatin, at two different contact times (48 and 96 h), using Petit Verdot, Malbec, and Cabernet Sauvignon wines. Turbidity, total phenolics, precipitable tannins, catechins, and color characteristics were determined. QP reduced the turbidity of all wines in a similar way to commercial fining agents. Both doses of QP significantly reduced tannins and other phenolic measures, including color intensity reductions, in a similar way to commercial fining agents. CONCLUSION QP behaved as an effective fining agent that deserves further studies in order to improve its performance and advance its characterization. © 2022 Society of Chemical Industry.

Pino‐Ramos, Liudis L.↗

DOE OSTI2023

A Simplified Approach Based on Cellular Automata for Describing Direct Reduced Iron Production in Different Reducing Conditions

A quick computation approach based on cellular automata is developed and implemented to describe the reduction of iron ore pellets by a mixture of reducing agents featured by different H 2 /CO ratios. The evolution of oxygen concentration inside the pellet is followed from the beginning to the end of contact between reducing agent and pellet. The variation of thermal state of pellets and gas mixture is computed based on their initial temperature, considering the heat involved and the convective heat exchange between pellet and gas mixture. The use of cellular automata and finite‐difference method to solve the diffusion equation point out the absence of any diffusion coefficient value, allowing to make the model fit the experimental trial, because the problem is that it is not ruled just by diffusion but also by the concentration variation of reducing agent inside the pellet due to porosity increasing during reduction. The updating of the reducing agents concentration implies a sharp decrease of oxygen concentration that the cellular automata model considers. The developed model is able to provide the in‐line control of reduction process and could be used to adjust the chemical concentration and temperature of injected reducing agents.

Metallurgy & Metallurgical Engineering↗

DOE OSTI2019

Nonlocal Flocking Dynamics: Learning the Fractional Order of PDEs from Particle Simulations

Flocking refers to collective behavior of a large number of interacting entities, where the interactions between discrete individuals produce collective motion on the large scale. We employ an agent-based model to describe the microscopic dynamics of each individual in a flock, and use a fractional partial differential equation (fPDE) to model the evolution of macroscopic quantities of interest. The macroscopic models with phenomenological interaction functions are derived by applying the continuum hypothesis to the microscopic model. Instead of specifying the fPDEs with an ad hoc fractional order for nonlocal flocking dynamics, we learn the effective nonlocal influence function in fPDEs directly from particle trajectories generated by the agent-based simulations. We demonstrate how the learning framework is used to connect the discrete agent-based model to the continuum fPDEs in one- and two-dimensional nonlocal flocking dynamics. In particular, a Cucker–Smale particle model is employed to describe the microscale dynamics of each individual, while Euler equations with nonlocal interaction terms are used to compute the evolution of macroscale quantities. The trajectories generated by the particle simulations mimic the field data of tracking logs that can be obtained experimentally. They can be used to learn the fractional order of the influence function using a Gaussian process regression model implemented with the Bayesian optimization. We show in one- and two-dimensional benchmarks that the numerical solution of the learned Euler equations solved by the finite volume scheme can yield correct density distributions consistent with the collective behavior of the agent-based system solved by the particle method. Furthermore, the proposed method offers new insights into how to scale the discrete agent-based models to the continuum-based PDE models, and could serve as a paradigm on extracting effective governing equations for nonlocal flocking dynamics directly from particle trajectories.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Structure of a benzylidene derivative of 9(10H)-anthracenone in complex with tubulin provides a rationale for drug design

Highlights: • The first crystal structure of an anthracenone family agent complexed with tubulin. • Comparison of the binding mode between different agents reveals the inhibition mechanism. • This structure helps understand the results of the structure-activity-relationship (SAR) studies. Microtubules are composed of αβ-tubulin heterodimers and have been treated as highly attractive targets for antitumor drugs. A broad range of agents bind to tubulin and interfere with microtubule assembly, including colchicine binding site inhibitors (CBSIs). Tubulin Polymerization Inhibitor I (TPI1), a benzylidene derivative of 9(10H)-anthracenone, is a CBSI that inhibits the assembly of microtubules. However, for a long time, the design and development of anthracenone family drugs have been hindered by the lack of structural information of the tubulin-agent complex. Here we report a 2.3 Å crystal structure of tubulin complexed with TPI1, the first structure of anthracenone family agents. This complex structure reveals the interactions between TPI1 and tubulin, and thus provides insights into the development of new anthracenone derivatives targeting the colchicine binding site.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Unsupported and carbon-supported silver catalysts for oxygen reduction reaction in alkaline media

Quick and easy Ag catalysts preparation via wet chemical synthesis method using only reducing agent (pure-Ag); reducing agent and citric acid as the capping agent (Ag-CA); and carbon support (KetjenBlack 600J), capping agent, and the reducing agent (Ag/C) is demonstrated. The Ag-based electrocatalysts are characterized by high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) with energy-dispersive X-ray spectroscopy (EDS), scanning electron microscopy (SEM), X-ray diffraction (XRD) analysis, and X-ray photoelectron spectroscopy (XPS). The electrocatalytic activity of Ag catalysts for O 2 reduction reaction (ORR) in 1 M KOH is evaluated using the rotating (ring)-disc electrode method. SEM and HAADF-STEM results show that the unsupported pure-Ag and Ag-CA catalysts consist mainly of big agglomerates, and Ag/C has the smallest agglomerates and some sub-3 nm Ag nanoparticles. The XPS results reveal that Ag in all the catalysts is in the metallic form (Ag 0 ). Despite consisting of big agglomerates, the Ag-CA catalyst exhibits similar ORR electrocatalytic activity to that of Ag/C. Ag-CA (unsupported) shows the lowest hydrogen peroxide yield. These results are of great importance for the development of Ag-based catalysts that can be prepared in a fast, simple and easily up scalable fashion, for anion exchange membrane fuel cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Synthesis of α-MoO{sub 3} nanoplates using organic aliphatic acids and investigation of sunlight enhanced photodegradation of organic dyes

Graphical abstract: Thermodynamically stable α-MoO{sub 3} nanoplates and nanorods were synthesized using organic structure controlling agents and demonstrated sun light enhanced photocatalytic degradation of methylene blue (MB) and rhodamine blue (Rh-B) dyes in aqueous solution. - Highlights: • α-MoO{sub 3} hexagonal nanoplates using organic structure controlling agents. • Tunable optical band gap of MoO{sub 3}. • Demonstrated strong sun light mediated enhanced photodegradation of methylene blue and rhodamine blue. • Photodegradation did not use any other external oxidizing agents. - Abstract: Thermodynamically stable α-MoO{sub 3} nanoplates were synthesized using organic aliphatic acids as structure controlling agents and investigated photocatalytic degradation of methylene blue (MB) and rhodamine blue (Rh-B) in presence of sun light. Three different organic aliphatic acids, citric acid (CA), tartaric acid (TA) and ethylene diamine tetra-acetic acid (EDTA), were employed to control morphologies. CA and TA predominantly produced extended hexagonal plates where EDTA gave nanorods as well as nanoplates. PXRD studies confirmed the formation of α-MoO{sub 3} nanoparticles. HR-TEM and FE-SEM reveal the formation of plate morphologies with 20–40 nm thickness, 50–100 nm diameter and 600 nm lengths. The different morphologies of α-MoO{sub 3} nanoparticles lead to the tunable optical band gap between 2.80 and 2.98 eV which was obtained from diffused reflectance spectra (DRS). Interestingly, the synthesized α-MoO{sub 3} nanoplates exhibited strong photocatalytic degradation of MB and Rh-B up to 99% in presence of sun light without using any oxidizing agents.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Goniothalamin prevents the development of chemically induced and spontaneous colitis in rodents and induces apoptosis in the HT-29 human colon tumor cell line

Colon cancer is the third most incident type of cancer worldwide. One of the most important risk factors for colon cancer development are inflammatory bowel diseases (IBD), thus therapies focusing on IBD treatment have great potential to be used in cancer prevention. Nature has been a source of new therapeutic and preventive agents and the racemic form of the styryl-lactone goniothalamin (GTN) has been shown to be a promising antiproliferative agent, with gastroprotective, antinociceptive and anti-inflammatory effects. As inflammation is a well-known tumor promoter, the major goal of this study was to evaluate the therapeutic and preventive potentials of GTN on chemically induced and spontaneous colitis, as well as the cytotoxic effects of GTN on a human colon tumor cell line (HT-29). GTN treatments inhibited TNBS-induced acute and chronic colitis development in Wistar rats, reducing myeloperoxidase levels and inflammatory cells infiltration in the mucosa. In spontaneous-colitis using IL-10 deficient mice (C57BL/6 background), GTN prevented colitis development through downregulation of TNF-α, upregulation of SIRT-1 and inhibition of proliferation (PCNA index), without signs of toxicity after three months of treatment. In HT-29 cells, treatment with 10 μM of GTN induced apoptosis by increasing BAX/BCL2, p-JNK1/JNK1, p-P38/P38 ratios as well as through ROS generation. Caspase 8, 9 and 3 activation also occurred, suggesting caspase-dependent apoptotic pathway, culminating in PARP-1 cleavage. Together with previous data, these results show the importance of GTN as a pro-apoptotic, preventive and therapeutic agent for IBD and highlight its potential as a chemopreventive agent for colon cancer. - Highlights: • Goniothalamin (GTN) inhibits the development of TNBS-induced colitis in rats. • Moreover, GTN prevents the development of spontaneous colitis in IL-10 deficient mice. • This activity relies on downregulation of TNF-α and upregulation of SIRT-1 expression. • GTN induces intrinsic apoptosis in HT-29 cells, involving ROS, MAPK and caspases. • These results highlight GTN as a potential chemopreventive agent for colon cancer.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Odorous gaseous emissions as influence by process condition for the forced aeration composting of pig slaughterhouse sludge

Highlights: • The gaseous emissions produced by various composting process conditions were characterized and quantified. • Nine compounds were potentially odorous: TMA, NH{sub 3}, 2-pentanone, 1-propanol-2-methyl, acetophenone and sulphur forms. • The tested composting process conditions reduced odour emissions by a factor of 5–10. • A reduction of 10{sup 5} to 10{sup 6} is required to reach an odour threshold limit at peak event emissions. • Both aeration rate and bulking agent had the most impact on reducing odour emissions. - Abstract: Compost sustainability requires a better control of its gaseous emissions responsible for several impacts including odours. Indeed, composting odours have stopped the operation of many platforms and prevented the installation of others. Accordingly, present technologies collecting and treating gases emitted from composting are not satisfactory and alternative solutions must be found. Thus, the aim of this paper was to study the influence of composting process conditions on gaseous emissions. Pig slaughterhouse sludge mixed with wood chips was composted under forced aeration in 300 L laboratory reactors. The process conditions studied were: aeration rate of 1.68, 4.03, 6.22, 9.80 and 13.44 L/h/kg of wet sludge; incorporation ratio of 0.55, 0.83 and 1.1 (kg of wet wood chips/kg of wet sludge), and; bulking agent particles size of <10, 10 < 20 and 20 < 30 mm. Out-going gases were sampled every 2 days and their composition was analysed using gas chromatography coupled with mass spectrometry (GC–MS). Fifty-nine compounds were identified and quantified. Dividing the cumulated mass production over 30 days of composting, by odour threshold, 9 compounds were identified as main potential odour contributors: hydrogen sulphide, trimethylamine, ammonia, 2-pentanone, 1-propanol-2-methyl, dimethyl sulphide, dimethyl disulphide, dimethyl trisulphide and acetophenone. Five gaseous compounds were correlated with both aeration rate and bulking agent to waste ratio: hydrogen sulphide, trimethylamine, ammonia, 2-pentanone and 1-propanol-2-methyl. However, dropping the aeration rate and increasing the bulking agent to waste ratio reduced gaseous odour emissions by a factor of 5–10, when the required threshold dilution factor ranged from 10{sup 5} to 10{sup 6}, to avoid nuisance at peak emission rates. Process influence on emissions of dimethyl sulphide, dimethyl disulphide, dimethyl trisulphide were poorly correlated with both aeration rate and bulking agent to waste ratio as a reaction with hydrogen sulphide was suspected. Acetophenone emissions originated from the wood chips. Olfactory measurements need to be correlated to gaseous emissions for a more accurate odour emission evaluation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Molecular Interaction Regulates the Performance and Longevity of Defect Passivation for Metal Halide Perovskite Solar Cells

Defect passivation constitutes one of the most commonly used strategies to fabricate highly efficient perovskite solar cells (PSCs). However, the durability of the passivation effects under harsh operational conditions has not been extensively studied regardless of the weak and vulnerable secondary bonding between the molecular passivation agents and perovskite crystals. Here, we incorporated strategically designed passivating agents to investigate the effect of their interaction energies on the perovskite crystals and correlated these with the performance and longevity of the passivation effects. We unraveled that the passivation agents with a stronger interaction energy are advantageous not only for effective defect passivation but also to suppress defect migration. The prototypical PSCs treated with the optimal passivation agent exhibited superior performance and operational stability, retaining 81.9 and 85.3% of their initial performance under continuous illumination or nitrogen at 85 °C after 1008 h, respectively, while the reference device completely degraded during that time. Furthermore, this work provides important insights into designing operationally durable defect passivation agents for perovskite optoelectronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

A Reinforcement Learning Approach to Augment Conventional PID Control in Nuclear Power Plant Transient Operation

The ability of nuclear reactors to operate their power conversion cycles more flexibly will enhance their value to energy grids with variable pricing. Current nuclear control systems are typically classical controllers that are often based on proportional-integral-derivative (PID) control. This paper presents a method of augmenting the existing PID control for difficult transient operations in nuclear power plants using a reinforcement learning–derived feedforward signal applied in real time. The agents, which are trained on a test thermal load-following problem, are designed to improve steam generator outlet temperature control for a range of fast load-following scenarios covering ramp rates from 9%/min to 15%/min. Several reinforcement learning algorithms were initially investigated for the training of the feedforward agents with deep Q-learning (DQN) and proximal policy optimization (PPO) networks, which were found to be the most promising. The DQN controllers utilize discrete actions, giving them a better disturbance rejection at steady state but inconsistent response to initial temperature deviations. In contrast, PPO-trained agents, which take continuous actions except for a dead zone around zero, were shown to have the best combination of high disturbance rejection at steady state and good tracking of the desired temperature value. The ability of the PPO agent was also examined, with the average time of decision making found to be on the order of 1 ms. The fault properties of the controller under the loss of the reinforcement learning agent feedforward signal were also examined. The controller showed strong performance in situations of “no-signal” faults. but was less good at handling “stuck-at” faults, where the feedforward signal remains at a set value. In both cases, however, the PID was able to successfully maintain stability, eventually returning the system to a steady state. It is hoped that this work will allow for the proposed control architecture to be examined for more difficult control problems such that it may eventually be used to adapt existing nuclear plants for more aggressive load-following on grids of the future.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Monotonicity in the averaging process

In this work, we investigate an averaging process that describes how interacting agents approach consensus through binary interactions. In each elementary step, two agents are selected at random and they reach compromise by adopting their opinion average. We show that the fraction of agents with a monotonically decreasing opinion decays as e - αt , and that the exponent is selected as the extremum from a continuous spectrum of possible values. The opinion distribution of monotonic agents is asymmetric, and it becomes self-similar at large times. Furthermore, the tails of the opinion distribution are algebraic, and they are characterized by two distinct and nontrivial exponents. We also explore statistical properties of agents with an opinion strictly above average.

97 MATHEMATICS AND COMPUTING↗