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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 325 records · Page 18

A Privacy Preserving Distributed Model Identification Algorithm for Power Distribution Systems: Preprint

Distributed control/optimization is a promising approach for network systems due to its advantages over centralized schemes, such as robustness, cost-effectiveness, and improved privacy. However, distributed methods can have drawbacks, such as slower convergence rates due to limited knowledge of the overall network model. Additionally, ensuring privacy in the communication of sensitive information can pose implementation challenges. To address this issue, we propose a distributed model identification algorithm that enables each agent to identify the sub-model that characterizes the relationship between its local control and the overall system outputs. The proposed algorithm maintains the privacy of local agents by only communicating through dummy variables. We demonstrate the efficacy of our algorithm in the context of power distribution systems by applying it to the voltage regulation of a modified IEEE distribution system. The proposed algorithm is well-suited to the needs of power distribution controls and offers an effective solution to the challenges of distributed model identification in network systems.

data-driven modeling↗

BETO 2021 Peer Review - Cyanobacteria Photosynthetic Energy Platform (1.3.4.301)

Cyanobacteria Photosynthetic Energy Platform (WBS 1.3.4.301) The primary challenge in algal technology is low energy conversion efficiency, currently up to a few percentages from photon energy to biomass energy. Most incoming solar energy is lost in the processes of photosynthesis, through mechanisms that are not fully understood. There is large room for improvement. This project develops cyanobacteria genetic tools to improve photosynthetic efficiency and biomass productivity through manipulation of energy regulation mechanisms. Increasing algal biomass productivity by 20% translates to $2 reduction of MFSP. Genetic manipulation is an essential tool in understanding and improving algal productivity. While genetic manipulation is challenging for most algae, model cyanobacteria, with in-house mutant library and genetic engineering toolboxes, allow for rapid hypothesis testing and transfer of lessons to other cyanobacteria and eukaryotic algae. We developed Energome (energy-ome) concept to guide novel engineering strategies and unleash unused potential in photosynthesis. Energome consists of cellular energy management mechanisms. For example, we found that cyanobacteria use futile cycles around glycogen and sucrose to dissipate ATP. By genetic modification, the model cyanobacterium Synechocystis 6803 showed higher energy levels, increased photosynthetic capacity, and 20% improvement in biomass yield in simulated outdoor light conditions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A review of methods for the reconstruction and analysis of integrated genome-scale models of metabolism and regulation

The current survey aims to describe the main methodologies for extending the reconstruction and analysis of genome-scale metabolic models and phenotype simulation with Flux Balance Analysis mathematical frameworks, via the integration of Transcriptional Regulatory Networks and/or gene expression data. Although the surveyed methods are aimed at improving phenotype simulations obtained from these models, the perspective of reconstructing integrated genome-scale models of metabolism and gene expression for diverse prokaryotes is still an open challenge.

59 BASIC BIOLOGICAL SCIENCES↗

Harnessing plant‐based platform for low‐cost cellulosic sugar recovery from bioenergy crops

The price of pure cellulase enzyme for the recovery of fermentable cellulosic sugars is one of the major challenges that limit the commercialization of second-generation biofuels and bio-based products. This work shows a means to greatly reduce the cost of cellulases. The abundant capacity of plants to synthesize and hyperaccumulate transgenic proteins in their plastids has been demonstrated for two gene constructs using either NPT II or Tet C to regulate the expression of bacterial cellulase Cel6A. Previously, the expression of Cel6A to 20–35% of total soluble leaf protein in tobacco was shown in two consecutive field trials. Moving forward, the key challenge was the extraction of active enzymes from the transgenic tobacco leaves hyperaccumulating bacterial cellulases in a cost-effective manner. The study showed that unpurified crude extracts of NPT II and Tet C transgenic tobacco leaves recovered ~23% and ~29% w/w cellulosic sugars from energycane bagasse, respectively. A supplementation of as low as 25% of purified commercial cellulase improved the glucose recovery by 2.9 times (~85% w/w) compared to 100% crude extract, which is comparable to the glucose recovery obtained by commercial cellulases, thereby suggesting a reduced requirement of commercial cellulases leading to a cost reduction of 75% for biorefineries. Assuming a stable 40% cellulase yield in total soluble protein under field conditions and multiple harvests (one to three) a year, the study estimates that the potential cost for saccharification of 1 t of lignocellulosic biomass can be reduced to 67–200 USD by using crude leaf extracts of transgenic tobacco.

biofuel↗

Uncertainty quantification of a physics-informed model based on sparse identification of a Thermal Energy Distribution System

Integrated energy systems (IES)s are crucial for enhancing the economy and efficiency of power generation sources (e.g., nuclear energy) necessary to unleash American energy dominance. These systems can be integrated with thermal energy storage (TES) and intermittent renewable energies to optimize overall energy use, peak-load regulation, and demand-side responses. However, the stabilization of energy generation, transport, and utilization introduces operational complexities that exceed the challenges of managing each sub-component individually. Currently, though IESs rely on human operators for efficiency and stability, reducing human error risk and enhancing performance through automation is highly desirable. Recent advances at Idaho National Laboratory have demonstrated successful control of the Thermal Energy Distributed System (TEDS). However, the automatic control system depends on a deterministic Sparse Identification of Nonlinear Dynamics with Control (SINDyC) model, which are trained based on simulation data from physics-based simulations. Because of uncertainties in physics-based simulation, SINDyC model results in large discrepancies against experimental data and cannot be reliably used in automatic control. In this paper, we present an innovative approach to address these discrepancies by quantifying uncertainties and developing a more robust model. We first generated trajectories by using first-principles physics codes to encapsulate the experiment. Next, we trained thousands of models by randomly sampling these trajectories. We then collapsed all those models into one probabilistic SINDyC by fitting a multivariate Gaussian distribution onto the resulting coefficient’s distribution. Despite its simplicity, our approach successfully produced 95% confidence intervals that captured the experimental trajectories. It even did so with a higher probability and better U-pooling score across six of the seven relevant quantities of interest (QoIs), as compared to other classical approaches. In conclusion, ongoing research is focusing on generating new experimental trajectories to validate this approach, and on employing Bayesian calibration to refine parametric uncertainties and guide future model development efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Mapping protein dynamics at high spatial resolution with temperature-jump X-ray crystallography

Understanding and controlling protein motion at atomic resolution is a hallmark challenge for structural biologists and protein engineers because conformational dynamics are essential for complex functions such as enzyme catalysis and allosteric regulation. Time-resolved crystallography offers a window into protein motions, yet without a universal perturbation to initiate conformational changes the method has been limited in scope. Here we couple a solvent-based temperature jump with time-resolved crystallography to visualize structural motions in lysozyme, a dynamic enzyme. We observed widespread atomic vibrations on the nanosecond timescale, which evolve on the submillisecond timescale into localized structural fluctuations that are coupled to the active site. An orthogonal perturbation to the enzyme, inhibitor binding, altered these dynamics by blocking key motions that allow energy to dissipate from vibrations into functional movements linked to the catalytic cycle. Because temperature jump is a universal method for perturbing molecular motion, the method demonstrated here is broadly applicable for studying protein dynamics.

59 BASIC BIOLOGICAL SCIENCES↗

Power-Sharing between Grid-Forming and Grid-Following Inverters

Power-sharing between the grid-forming and the grid-following inverter in a small microgrid is a challenging task. Specifically, the decentralized droop-based power-sharing is difficult to achieve when the grid-forming inverter regulates the voltage and the frequency. This article proposes controllers for the grid-forming and the grid-following inverters, which ensure proportional power-sharing as well as regulate the voltage and the frequency. Both controllers use active power-frequency and reactive power-voltage droops. Additional secondary loops and secondary forward paths are added to the controller of the grid-forming inverter and the grid-following inverter, respectively, to ensure simultaneous voltage and frequency regulation and power-sharing. The efficacy of the proposed controllers for power-sharing is verified through experiment results in a multi-inverter testbed.

Sadeque, Fahmid↗

Alternative Pozzolans for Replacement of Fly Ash in Grout: Literature Review for Continuous Improvement of Cement Waste Forms

The Department of Energy (DOE) is currently responsible for treating radioactive and mixed waste, performing environmental restoration, and closing contaminated tanks and facilities resulting from nuclear weapons production during the Cold War. Cementitious reagents are the most widely used materials for (1) chemically stabilizing and encapsulating radionuclides and hazardous metals and (2) solidifying radioactive wastewater. Cementitious grouts and flowable concretes are also the most widely used materials for tank and facility closures and are used extensively for physical as well as chemical stabilization in environmental restoration projects. Ambient temperature radioactive waste cementation is a widely used technology for producing waste forms for final disposal. The current practice of designing and testing waste forms is based on a mid to late 20th century technology approach (i.e., materials, characterization, and test methods) for generating parameters for risk assessments. DOE technology development is needed to address both current, long-term, and emerging issues in this area as new waste streams come online and as regulations, performance knowledge, and risk assessment methodology continue to evolve. Consequently, the use of cementation as a means of treating chemically challenging radioactive liquid waste streams and reactive debris requires an enduring effort.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Conformation-specific synthetic intrabodies modulate mTOR signaling with subcellular spatial resolution

Subcellular compartmentalization is integral to the spatial regulation of mechanistic target of rapamycin (mTOR) signaling. However, the biological outputs associated with location-specific mTOR signaling events are poorly understood and challenging to decouple. Here, we engineered synthetic intracellular antibodies (intrabodies) that are capable of modulating mTOR signaling with genetically programmable spatial resolution. Epitope-directed phage display was exploited to generate high affinity synthetic antibody fragments (Fabs) against the FKBP12–Rapamycin binding site of mTOR (mTOR FRB ). We determined high-resolution crystal structures of two unique Fabs that discriminate distinct conformational states of mTOR FRB through recognition of its substrate recruitment interface. By leveraging these conformation-specific binders as intracellular probes, we uncovered the structural basis for an allosteric mechanism governing mTOR complex 1 (mTORC1) stability mediated by subtle structural adjustments within mTOR FRB . Furthermore, our results demonstrated that synthetic binders emulate natural substrates by employing divergent yet complementary hydrophobic residues at defined positions, underscoring the broad molecular recognition capability of mTOR FRB . Intracellular signaling studies showed differential time-dependent inhibition of S6 kinase 1 and Akt phosphorylation by genetically encoded intrabodies, thus supporting a mechanism of inhibition analogous to the natural product rapamycin. Finally, we implemented a feasible approach to selectively modulate mTOR signaling in the nucleus through spatially programmed intrabody expression. These findings establish intrabodies as versatile tools for dissecting the conformational regulation of mTORC1 and should be useful to explore how location-specific mTOR signaling influences disease progression.

Science & Technology - Other Topics↗

Cybersecurity for Distributed Energy Resources: All Hazards Approach for Grid Modernization

Distributed energy resources (DER) sit at the intersection of IoT and critical infrastructure. As we work towards clean energy and decarbonization targets, high rates of growth of DER are expected, making them an important component of generation and grid services. They have been a part of the explosion of internet connected devices developed to solve real-world problems and make life easier by providing clean, local energy and enable the smart management of grid services. However, the quick-to-market, low-cost drivers for DER, combined with a historically relative low-impact has meant that cybersecurity has not been a top priority. So as DER penetration increases, will DER be a part of the growing challenge of securing the grid, or part of the solution for necessary grid modernization? In this talk, we will discuss the factors that have led to our current position and what makes cybersecurity for DER unique. A wide range of research is conducted at national labs, in partnership with industry and academia, to inform everything from standards and regulation, to the development of cyber-physical anomaly detection through use of digital twins, and even advanced threat analytics to SBOM and HBOM tracking. Even with this multi-faceted approach to the challenges, the question remains: is this too little too late or are we doing enough to secure the grid for the next 30 years?

14 SOLAR ENERGY↗

Challenges and Opportunities Associated with the Municipal Solid Waste

Municipal solid waste (MSW) is one of the important challenges in today’s world. A continuous surge in population, increasing living standards, and rapid urbanization are generating an enormous quantity of MSW. Improper management of this MSW often leads to the release of greenhouse gases, emission of particulate matters, and formation of dioxins, which all ultimately contributes to climate change. Recycling these wastes via landfills with gas recovery and/or energy and material production via thermal and chemical conversions could be viable options to manage these challenges. Recycling of MSW is difficult because it is very heterogeneous in nature. The heterogeneity of MSW varies significantly from country to country and from one municipality to another. Such variation depends mainly on the waste management regulations and industrial structure of each region. The quantity and the quality of MSW are critical for determination of the handling and management. This presentation will discuss the statistics (e.g., source, quantity, quality, etc.) of MSW following by the current state-of-the-art technologies for handling those wastes. The key challenges handling those wastes and possible improvements of the handling processes will be discussed further. Finally, the potential opportunities for MSW, especially the contributions to the bio-energy field, will be discussed.

09 BIOMASS FUELS↗

Transcriptional competition shapes proteotoxic ER stress resolution

Through dynamic activities of conserved master transcription factors (mTFs), the unfolded protein response (UPR) relieves proteostasis imbalance of the endoplasmic reticulum (ER), a condition known as ER stress. Because dysregulated UPR is lethal, the competence for fate changes of the UPR mTFs must be tightly controlled. However, the molecular mechanisms underlying regulatory dynamics of mTFs remain largely elusive. Here, we identified the abscisic acid-related regulator G-class bZIP TF2 (GBF2) and the cis-regulatory element G-box as regulatory components of the plant UPR led by the mTFs, bZIP28 and bZIP60. We demonstrate that, by competing with the mTFs at G-box, GBF2 represses UPR gene expression. Conversely, a gbf2 null mutation enhances UPR gene expression and suppresses the lethality of a bzip28 bzip60 mutant in unresolved ER stress. Here, by demonstrating that GBF2 functions as a transcriptional repressor of the UPR, we address the long-standing challenge of identifying shared signalling components for a better understanding of the dynamic nature and complexity of stress biology. Furthermore, our results identify a new layer of UPR gene regulation hinged upon an antagonistic mTFs-GFB2 competition for proteostasis and cell fate determination.

59 BASIC BIOLOGICAL SCIENCES↗

Assessing the Optimality of LinDist3Flow for Optimal Tap Selection of Step Voltage Regulators in Unbalanced Distribution Networks: Preprint

The adoption of distributed energy resources such as photovoltaics (PVs) has increased dramatically during the previous decade. The increased penetration of PVs into distribution networks (DNs) can cause voltage fluctuations that have to be mitigated. One of the key utility assets employed to this end are step-voltage regulators (SVRs). It is desirable to include tap selection of SVRs in optimal power flow (OPF) routines, a task that turns out to be challenging because the resultant OPF problem is nonconvex with added complexities stemming from accurate SVR modeling. While several convex relaxations based on semi-definite programming (SDP) have been presented in the literature for optimal tap selection, SDP based schemes do not scale well and are challenging to implement in large-scale planning or operational frameworks. This paper deals with the optimal tap selection (OPTS) problem for wye-connected SVRs using linear approximations of power flow equations. Specifically, the LinDist3Flow model is adopted and the effective SVR ratio is assumed to be continuous–enabling the formulation of a problem called LinDist3Flow-OPTS, which amounts to a linear program. The scalability and optimality gap of LinDist3Flow-OPTS are evaluated with respect to existing SDP-based and nonlinear programming techniques for optimal tap selection in three standard feeders, namely, the IEEE 13-bus, 123-bus, and 8500-node DNs. For all DNs considered, LinDist3Flow-OPTS achieves an optimality gap of approximately 1% or less while significantly lowering the computational burden.

linear approximations↗

Assessing the Optimality of LinDist3Flow for Optimal Tap Selection of Step Voltage Regulators in Unbalanced Distribution Networks

The adoption of distributed energy resources such as photovoltaics (PVs) has increased dramatically during the previous decade. The increased penetration of PVs into distribution networks (DNs) can cause voltage fluctuations that have to be mitigated. One of the key utility assets employed to this end are step-voltage regulators (SVRs). It is desirable to include tap selection of SVRs in optimal power flow (OPF) routines, a task that turns out to be challenging because the resultant OPF problem is nonconvex with added complexities stemming from accurate SVR modeling. While several convex relaxations based on semi-definite programming (SDP) have been presented in the literature for optimal tap selection, SDP based schemes do not scale well and are challenging to implement in large-scale planning or operational frameworks. This paper deals with the optimal tap selection (OPTS) problem for wye-connected SVRs using linear approximations of power flow equations. Specifically, the LinDist3Flow model is adopted and the effective SVR ratio is assumed to be continuous- enabling the formulation of a problem called LinDist3Flow-OPTS, which amounts to a linear program. The scalability and optimality gap of LinDist3Flow-OPTS are evaluated with respect to existing SDP-based and nonlinear programming techniques for optimal tap selection in three standard feeders, namely, the IEEE 13-bus, 123-bus, and 8500-node DNs. For all DNs considered, LinDist3Flow-OPTS achieves an optimality gap of approximately 1% or less while significantly lowering the computational burden.

linear approximations↗

Regulation of Surface Defect Chemistry toward Stable Ni-Rich Cathodes

Surface reconstruction of Ni-rich layered oxides (NLO) degrades the cycling stability and safety of high-energy-density lithium-ion batteries (LIBs), which challenges typical surface-modification approaches to build a robust interface with electrochemical activity. Here, a strategy of leveraging the low-strain analogues of Li- and Mn-rich layered oxides (LMR) to reconstruct a stable surface on the Ni-rich layered cathodes is proposed. The new surface structure not only consists of a gradient chemical composition but also contains a defect-rich structure regarding the formation of oxygen vacancies and cationic ordering, which can simultaneously facilitate lithium diffusion and stabilize the crystal structure during the (de)lithiation. These features in the NLO lead to a dramatic improvement in electrochemical properties, especially the cyclability under high voltage cycling, exhibiting the 30% increase in capacity retention after 200 cycles at the current density of 1 C (3.0-4.6 V). We report the findings offer a facile and effective way to regulate defect chemistry and surface structure in parallel on Ni-rich layered structure cathodes to achieve high-energy density LIBs.

25 ENERGY STORAGE↗

Molecular Recognition with Resolution Below 0.2 Angstroms Through Thermoregulatory Oscillations in Covalent Organic Frameworks

Crystalline materials with uniform molecular-sized pores are desirable for a broad range of applications, such as sensors, catalysis, and separations. However, it is challenging to tune the pore size of a single material continuously and to reversibly distinguish small molecules (below 4 angstroms). We synthesized a series of ionic covalent organic frameworks using a tetraphenoxyborate linkage that maintains meticulous synergy between structural rigidity and local flexibility to achieve continuous and reversible (100 thermal cycles) tunability of “dynamic pores” between 2.9 and 4.0 angstroms, with resolution below 0.2 angstroms. This results from temperature-regulated, gradual amplitude change of high-frequency linker oscillations. These thermoelastic apertures selectively block larger molecules over marginally smaller ones, demonstrating size-based molecular recognition and the potential for separating challenging gas mixtures such as oxygen/nitrogen and nitrogen/methane.

crystalline materials↗

Voluntary Renewable Energy Procurement Programs in Regulated Utility Markets

Multinational corporations are increasingly purchasing renewable energy (RE) to fulfill international commitments, reduce supply chain emissions, limit environmental impact, and secure stable and affordable electricity. The potential scale of global corporate RE purchasing has been estimated to be nearly 100 GW and growing; however, many markets still lack supportive enabling environments for corporations to access RE through on-site project development or private sector transactions. Even where allowed by law, on-site generation may be insufficient due to space and technical constraints, introducing additional challenges. Utility green pricing and utility green tariff programs backed by renewable energy certificates (RECs), referred to as utility green procurement programs (GPPs) in this report, offer powerful market-based solutions to utilities, regulators, and policymakers to provide corporate and other consumers with RE product options while generating revenue to support RE development. As RE markets expand around the globe, GPPs have proven to be effective mechanisms in market regimes, ranging from fully integrated state-owned utilities to broadly liberalized power markets. GPPs utilize RECs, which are a type of energy attribute certificate and closely resemble guarantees of origin, to track and ultimately monetize RE attributes that corporations and other buyers must procure to demonstrate progress against their RE commitments and make public claims of RE use. Time-tested and transparent REC accounting mechanisms provide market confidence, while at the same time offering flexibility to utilities, regulators, and customers for a range of applications. RECs are used in all types of electricity market structures, as indicated in Figure 1, but REC-based program designs and supporting components differ depending on the type of market. Liberalized markets allow for customers to contract directly with generators for electricity and RECs, while traditionally regulated markets with vertically integrated utility structures may have greater restrictions on generation asset ownership and electricity sales. RE markets can be further defined as being either mandatory or voluntary. Mandatory markets require suppliers to deliver specified amounts of RE to grid customers, such as under a renewable portfolio standard (RPS), while voluntary markets involve no legal mandates, but demand is driven by self-imposed customer goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Macromolecular gelatin properties affect fibrin microarchitecture and tumor spheroid behavior in fibrin-gelatin gels

The biophysical properties of extracellular matrices (ECM) are known to regulate cell behavior, however decoupling cell behavior changes due to the relative contributions of material microstructure versus biomechanics or nutrient permeability remains challenging, especially within complex, multi-material matrices. We developed four gelatin-fibrin interpenetrating network (IPN) formulations which are identical in composition but possess variable gelatin molecular weight distributions, and display differences in microstructure, biomechanics, and diffusivity. In this work we interrogate the response of multicellular tumor spheroids to these IPN formulations and found that a high stiffness, gelatin-network dominated IPNs impeded remodeling and invasion of multicellular tumor spheroids; whereas relatively lower stiffness, fibrin-network dominated IPNs permitted protease-dependent remodeling and spheroid invasion. Cell proliferation correlated to nutrient diffusivity across tested IPN formulations. These findings demonstrate the complexity of ECM IPNs, relative to single polymer matrices, and highlight that cell response does not derive from a single aspect of the ECM, but rather from the interplay of multiple biomechanical properties. The methodology developed in this study represents a framework for future studies which aim to characterize cellular phenotypic responses to biophysical cues present within complex, multi-material matrices.

36 MATERIALS SCIENCE↗