Physics-based Reduction with Monitoring Data Assimilation for Adaptive Representations in Structural Systems.
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This paper surveys the existing landscape of standards relevant to heliostats, identifies their gaps, and proposes a path forward to a comprehensive set of heliostat guidelines, technical specifications, and standards under the framework of International Electrotechnical Commission (IEC) TC 117. Gaps in existing guidelines and standards are surveyed using a three-tiered taxonomy: component-level, heliostat-level, and field-level. At each level, the gap analysis is followed by a proposal for a coordinated path forward on the development of standards. At the component level, advances in the understanding of wind loading should inform a technical specification for drives and structures. Reflectors require consolidation of measurement guidelines into existing standards documents. Communications & controls require technical standards to inform their selection and secure implementation. At the heliostat level, IEC 62817 (solar trackers) adequately characterizes drive systems, structures, and electronics, but requires adaptation to heliostats' use patterns, operating modes, and expected life cycles. IEC 62817 does not address heliostat beam quality and pointing accuracy, but the process for determining both is elaborated in the SolarPACES Guideline for Heliostat Performance Testing. This SolarPACES document requires two main modifications: adaptation to IEC language and inclusion of testing after heliostats which have undergone accelerated weathering and mechanical cycling (to understand performance degradation). At the field level, IEC 62862-4-2 addresses the function and control of heliostat fields but does not cover the statistically rigorous testing of heliostat groups, or field performance factors like security and soiling. The addition of documents under IEC-62862-4 is proposed to address this gap.
Oceans are a harsh environment and can impose significant loads on deployed structures. Deployment of wave energy converters (WECs) faces a design challenge with apparently contradictory goals. A WEC should be designed to maximize the energy absorbed while ensuring the operating wave condition does not exceed the failure limits of the device itself. Therefore, the loads endured by the support structure are a design constraint for the system. Adaptability to different sea states is, therefore, highly desirable. This work uses a WEC-Sim model of a Variable Geometry Oscillating Wave Energy Converter (VGOSWEC) mounted on a support structure simulated under different wave scenarios. A VGOSWEC resembles a paddle pitching about a fixed hinge perpendicular to the incoming waves-fronts. Therefore, the hinge experiences loads perpendicular to its axis as it maintains its position. The geometry of the VGOSWEC was varied by opening a series of controllable flaps on the pitching paddle when the structure experiences threshold loads. Since opening the flaps lets the waves transmit through the paddle, it is hypothesized that opening the flaps should result in load shedding at the base of the support structure. This load shedding is achieved by reducing the moments about the hinge axis. This work compares the hydrodynamic coefficients, natural periods, and Response Amplitude Operators (RAOs) from completely closed to completely open configurations of the controllable flaps. These comparisons quantify the effects of letting the waves transmit through the VGOSWEC. This work shows that the completely open configuration can reduce the pitch and surge loads on the base of the support structure by as much as 80%. It was observed that at the paddle's resonance frequency, the loads on the structure increased substantially. This increase in loads can be mitigated by a rotational Power Take-off (PTO) damping about the hinge axis. Changing the rotational PTO damping was identified as an additional design parameter that can be used to control the loads experienced by the WEC's support structure.
Oceans are harsh environments and can impose significant loads on deployed structures. The deployment of wave energy converters (WECs) faces a design challenge with apparently contradictory goals. A WEC should be designed to maximize the energy absorbed while ensuring the operating wave condition does not exceed the failure limits of the device itself. Therefore, the loads endured by the support structure are a design constraint for the system. Adaptability to different sea states is, therefore, highly desirable. This work uses a WEC-Sim model of a variable-geometry oscillating wave energy converter (VGOSWEC) mounted on a support structure simulated under different wave scenarios. A VGOSWEC resembles a paddle pitching about a fixed hinge perpendicular to the incoming wave fronts. Therefore, the hinge experiences loads perpendicular to its axis as it maintains its position. The geometry of the VGOSWEC is varied by opening a series of controllable flaps on the pitching paddle when the structure experiences threshold loads. Because opening the flaps lets the waves transmit through the paddle, it is hypothesized that opening the flaps should result in load shedding at the base of the support structure. The load shedding is achieved by reducing the moments about the hinge axis. This work compares the hydrodynamic coefficients, natural periods, and response amplitude operators from completely closed to completely open configurations of the controllable flaps. The comparisons quantify the effects of letting the waves transmit through the VGOSWEC. This work shows that the completely open configuration can reduce the pitch and surge loads on the base of the support structure by as much as 80%. It was observed that at the paddle's resonance frequency, the loads on the structure increased substantially. This increase in loads can be mitigated by a rotational power take-off damping about the hinge axis. Changing the rotational power take-off damping was identified as an additional design parameter that can be used to control the loads experienced by the WEC's support structure.
An adsorptive cooling system includes two highly adsorptive structures positioned to receive thermal energy from a thermal energy source, each highly adsorptive structure includes a substrate and a metal-organic framework (MOF) coupled to the respective substrate and adapted for adsorbing and desorbing a refrigerant under predetermined thermodynamic conditions. The adsorptive cooling system includes a cooling unit and a circulation system adapted for circulating the refrigerant from one of the highly adsorptive structures to the cooling unit to provide cooling from the thermal energy source and to return the refrigerant from the cooling unit to the same or other highly adsorptive structure. Each substrate may include a plurality of microchannels, providing ingress and egress paths for a refrigerant, defined by grooves in a surface of the substrate nearest the MOF and/or surfaces of a plurality of microcapillaries of the substrate. The microchannels provide ingress and egress paths for a refrigerant.
LBNL researchers developed a template and companion guide for structuring distribution system plans. The template covers 10 key sections in utility distribution system plans and underlying topics: -Executive Summary -Planning Objectives -Current Distribution System -Planning Approach -Asst Management, Reliability and Resilience -O&M Expenses -Capacity Expansion Planning -Solution Identification -Cost-effectiveness -Implementation For each section in the template, the companion guide provides: a description of the topics covered and their importance; the type of content to include in the plan; an example utility approach; and references to other utility plans that serve as models for the topic.
The Department of Defense (DoD) faces the substantial challenge of cost-effectively retrofitting one to two installations per month, each comprising approximately 1,000 buildings, to improve resilience, reduce energy consumption, and enhance energy supply security. Achieving these objectives requires optimal system selection and effective risk mitigation during system integration. To address this need, we introduce Platform-Based Design (PBD), a structured, hierarchical methodology adapted from other industrial sectors to the domain of energy system retrofits. We demonstrate the effectiveness of PBD through a techno-economic feasibility study comparing geothermal-coupled thermal energy networks (TENs) with conventional energy systems for heating, cooling, and powering 17 buildings at Joint Base Andrews (JBA) in Maryland. Our analysis illustrates that the PBD approach enables rigorous, data-driven, sequential decision making, resulting in a family of Pareto-optimal systems, among which the TEN emerged as the most promising solution. The selected TEN design integrates geothermal borefields, heat recovery heat pumps, photovoltaic (PV) arrays, and battery storage. Compared to the baseline system – gas heating combined with air-source chillers – the proposed TEN reduces annual imported energy by 74% and peak electricity demand by 45%, achieves a levelized cost of energy of $\$0.210$/kWh, and substantially enhances resilience. Life-cycle costs increase by approximately 6%, and initial investment costs are about 2.5 times higher than the baseline. However, if central plant infrastructure, district loops, and utility-scale PV and battery systems are privately funded and operated, the initial investment would fall below the baseline system cost. Critical to achieving these significant performance improvements were detailed nonlinear dynamic simulations coupling geothermal heat transfer, energy system operation, and realistic feedback control logic. These simulations identified essential design modifications and control strategy refinements that substantially reduced energy use, peak demand, and compressor shortcycling, thereby improving durability and reliability—issues that would have been significantly more expensive to resolve during operation. Additionally, the verification step highlighted sensitivities to key design parameters that could reduce initial investment by approximately $\$2$ million and reduce annual life-cycle costs more than $\$300,000$. We recommend adopting the PBD methodology for future feasibility studies and TEN pilot projects to gain valuable operational experience. Furthermore, we recommend that DoD invest in transferring and scaling the PBD methodology to other installations. This entails developing standardized computational frameworks and component libraries as well as training industry in conducting PBD. Such investments would enable rapid, robust, reliable, and cost-effective retrofits, supporting DoD’s ambitious energy system modernization goals.
The software framework, AMReX, supports the development of block-structured adaptive mesh refinement (AMR) algorithms for solving systems of partial differential equations. AMR reduces the computational cost and memory footprint compared to a uniform mesh while preserving the essential local descriptions of different physical processes in complex multiphysics algorithms. AMR uses a hierarchical representation of the solution at multiple levels of resolution where the solution on each level is defined on the union of data containers at that resolution. These data containers, which represent the solution over a logically rectangular subregion of the domain, can contain field data defined on a mesh, Lagrangian particles or combinations of both. In addition to these basic data types, AMReX supports a multilevel embedded boundary representation of complex geometry; linear solvers for cell-centered and nodal data; asynchronous I/O in a native format readable by ParaView, VisIt and yt; and interfaces to hypre and PETSc solvers. AMReX enables applications to run on distributed memory architectures with multicore CPUs and with GPU accelerators. AMReX uses a lightweight abstraction layer that effectively hides the details of the architecture from the application. The framework currently supports CUDA, HIP and SYCL for GPU acceleration and OpenMP for multi-core CPU architectures.
Layer Li-B-C compounds have been shown to have feasible superconductivity. Using the adaptive genetic algorithm, we predict the structures of the Li-B-C system at 100 GPa. Here we identify several low-enthalpy metallic phases with stoichiometries of Li B 2 C, Li B 3 C, Li 2 BC 2 , Li 3 B 2 C 3 , Li 3 BC, and Li 5 BC. Using a fast screening method of electron-phonon interaction, we find that Li B 3 C is a promising candidate for superconductivity. The consecutive calculations using the full Brillouin zone confirm the existence of the strong electron-phonon coupling (EPC) in this system. The anharmonic B-C phonon modes near the zone center provide the major contribution to the EPC. The EPC constant is 1.40, and the estimated critical temperature is 22 K. In this paper, we indicate that superconductivity can also happen without a layered structural motif in the Li-B-C system. We also demonstrate an effective strategy for crystal structure prediction of superconducting materials.
Electronic structure calculations on small systems such as H 2 , H 2 O, LiH, and BeH 2 with chemical accuracy are still a challenge for the current generation of noisy intermediate-scale quantum (NISQ) devices. One of the reasons is that due to the device limitations, only minimal basis sets are commonly applied in quantum chemical calculations, which allows one to keep the number of qubits employed in the calculations at a minimum. However, the use of minimal basis sets leads to very large errors in the computed molecular energies as well as potential energy surface shapes. One way to increase the accuracy of electronic structure calculations is through the development of small basis sets better suited for quantum computing. In this work, we show that the use of adaptive basis sets, in which exponents and contraction coefficients depend on molecular structure, provides an easy way to dramatically improve the accuracy of quantum chemical calculations without the need to increase the basis set size and thus the number of qubits utilized in quantum circuits. As a proof of principle, we optimize an adaptive minimal basis set for quantum computing calculations on an H 2 molecule, in which exponents and contraction coefficients depend on the H—H distance, and apply it to the generation of H 2 potential energy surface on IBM-Q quantum devices. The adaptive minimal basis set reaches the accuracy of the double-zeta basis sets, thus allowing one to perform double-zeta quality calculations on quantum devices without the need to utilize twice as many qubits in simulations. This approach can be extended to other molecular systems and larger basis sets in a straightforward manner.
Oceans are harsh environments and can impose significant loads on deployed structures. A wave energy converter (WEC) should be designed to maximize the energy absorbed while ensuring the operating wave condition does not exceed the failure limits of the device itself. Therefore, the loads endured by the support structure are a design constraint for the system. Furthermore, the WEC should be adaptable to different sea states. Herethis work uses a WEC-Sim model of a variable-geometry oscillating wave energy converter (VGOSWEC) mounted on a support structure simulated under different wave scenarios. A VGOSWEC resembles a paddle pitching about a fixed hinge perpendicular to the incoming wave fronts. The geometry of the VGOSWEC is varied by opening a series of controllable flaps on the pitching paddle when the structure experiences threshold loads. It is hypothesized that opening the flaps should result in load shedding at the base of the support structure by reducing the moments about the hinge axis. This work compares the hydrodynamic coefficients, natural periods, and response amplitude operators from completely closed to completely open configurations of the controllable flaps. This work shows that the completely open configuration can reduce the pitch and surge loads on the base of the support structure by as much as 80%. Increased loads at the structure’s natural period can be mitigated by an axial power take-off damping acting as an additional design parameter to control the loads at the WEC’s support structure.
Predicting the binding affinity of ligands to protein pockets is key in the drug design pipeline. The flexibility of ligand-pocket motifs arises from a range of attractive and repulsive electronic interactions during binding. Accurately accounting for all interactions requires robust quantum-mechanical (QM) benchmarks, which are scarce for ligand-pocket systems. Additionally, disagreement between “gold standard” Coupled Cluster (CC) and Quantum Monte Carlo (QMC) methods casts doubt on many benchmarks for larger non-covalent systems. We introduce the “QUantum Interacting Dimer” (QUID) benchmark framework containing 170 non-covalent (non-)equilibrium systems modeling chemically and structurally diverse ligand-pocket motifs. Symmetry-adapted perturbation theory shows that QUID broadly covers non-covalent binding motifs and energetic contributions. Robust binding energies are obtained using complementary CC and QMC methods, achieving agreement of 0.5 kcal/mol. The benchmark data analysis reveals that several dispersion-inclusive density functional approximations provide accurate energy predictions, though their atomic van der Waals forces differ in magnitude and orientation. Contrarily, semiempirical methods and empirical force fields require improvements in capturing non-covalent interactions (NCIs) for out-of-equilibrium geometries. The wide span of NCIs, highly accurate interaction energies, and analysis of molecular properties take QUID beyond the “gold standard” for QM benchmarks of ligand-protein systems.
We have developed the massively parallel electronic structure code SPARC-X: a computational framework for performing Kohn-Sham Density Functional Theory (DFT) calculations that can scale linearly with the number of atoms in the system, while being able to leverage petascale and emerging exascale parallel computers to study chemical phenomena at unprecedented length and time scales. SPARC-X exploits a recent breakthrough in electronic structure methodologies: systematically improvable, strictly local, orthonormal, discontinuous real-space bases that efficiently and systematically capture the local chemistry of the system. With further adaptation using new machine-learning techniques and the use of the massively parallel Spectral Quadrature (SQ) electronic structure method, the algorithmic complexity and prefactor associated with DFT calculations involving semilocal as well as hybrid functionals are dramatically reduced. Using petascale computational resources, SPARC-X enables quantum mechanical simulations at length and time scales previously accessible only by empirical approaches, e.g., 1,000,000 atoms for a few picoseconds using semilocal functionals or 1,000 atoms for a few picoseconds using hybrid functionals. Using exascale resources, the sizes and times targeted are two orders of magnitude larger. Such a capability has applications in a wide variety of chemical sciences, including reactive interfaces where large length- and/or long time-scales are needed and traditional force fields fail. This is particularly important in dynamic catalysis, where bond breaking and formation must be understood in detail. We developed, tested, and employed the SPARC-X framework to understand the photocatalytic properties of TiO 2 nanoparticles, revealing finite size effects that cannot be captured with standard model systems or functionals. This integrated development and application strategy ensures that SPARC-X remains a robust, efficient, and scalable software package for quantum simulations on current petascale and emerging exascale computing resources.
Abstract Vegetation responds dynamically to local microclimates at both short and long time scales via mechanisms ranging from physiological behaviors, such as stomatal closure, to acclimation and adaptation. These responses influence the carbon, water, and energy cycles directly and are therefore crucial to understanding and predicting Earth system responses to a changing climate. Several recent studies have demonstrated that differences in microclimate can induce structural and functional acclimations, and potentially adaptations, within the same ecosystem. Such microclimate divergence can be caused by variability in slopes, disturbance history, or even localized resource availability. Ecosystem stressors such as low soil water availability, limited photoperiod, or high vapor pressure deficit have been shown to reveal the large impact of the subtle differences within these systems such as the number of sun versus shade leaves or differences in whole‐plant water acquisition and use. These findings highlight the linkages between plant canopy structure and ecosystem function, alongside the need for comprehensive analyses of vegetation within the broader context of its environment. This commentary addresses some of the key implications of ecosystem stress responses and accompanying acclimations across three ecosystem types for ecosystem ecology, plant physiology, ecohydrology and trait‐based modeling of vegetation‐climate dynamics.
This study explores the potential applications across various domains, including earthquake detection and warning systems, where the system’s sensitivity to ground vibrations can contribute to early seismic event detection. Additionally, the study paves the way of developing applications of VLC/T in mechanical vibration and stability analysis of engines and platforms, offering insights into structural integrity and performance optimization. These multifaceted applications underscore the adaptability and potential of VLC/T systems in diverse fields, heralding advancements in sensing, communication, and security technologies. To achieve this, in this study, Peak to Average Power Ratio (PAPR) is proposed to represent the impact of mechanical shocks and vibrations generated by several weights dropped onto the platform with which the receiver is fixed. Even though non-contact measurement methodology is preferred for various reasons, the proposed measurement campaign obtains the data in contact form; however, the system and signal model proposed in this study could easily be extended into non-contact form. Considering the fact that the proposed measurement campaign employs off-the-shelf products, it is cost-effective and very scalable.
The RNA-guided ribonuclease CRISPR-Cas13 enables adaptive immunity in bacteria and programmable RNA manipulation in heterologous systems. Cas13s share limited sequence similarity, hindering discovery of related or ancestral systems. Here, to address this, we developed an automated structural-search pipeline to identify an ancestral clade of Cas13 (Cas13an) and further trace Cas13 origins to defense-associated ribonucleases. Despite being one-third the size of other Cas13s, Cas13an mediates robust programmable RNA depletion and defense against diverse bacteriophages. However, unlike its larger counterparts, Cas13an uses a single active site for both CRISPR RNA processing and RNA-guided cleavage, revealing that the ancestral nuclease domain has two modes of activity. Discovery of Cas13an deepens our understanding of CRISPR-Cas evolution and expands opportunities for precision RNA editing, showcasing the promise of structure-guided genome mining.
Optimization for different tasks like material characterization, synthesis, and functional properties for desired applications over multi-dimensional control parameter and function spaces need a rapid strategic search through active learning. However, in all cases prior to optimization, the target material properties are assumed known and fixed, which mostly deviates from real-world scenarios in material synthesis. This can be critical for running expensive experiments on new materials, when the experimental results are fuzzy for any scientific outcomes due to improper target setting, ultimately wasting time and cost. The failure rate and cost are even higher over exploring on multi-target space, where we want to learn the pareto among multiple properties, to jointly optimize during material synthesis for desired applications. To address the challenge, here we introduce the human-operator attempt flexibility in the active learning based automated experiment framework, with generating multiple human assessed targets through a voting-based recommender system during real-time microscope measurements over the large material image space, sequentially learn/update multiple desired targets through a weighting system, and adaptively search in multiple material properties functional space for non-dominated pareto discoveries to maximize the custom structural similarity based acquisition function. We term this a multi-objective Bayesian optimized human assessed multi-target generated spectral recommender systems (MOBO-HAM-SRS). The approach has been demonstrated to peizoresponse force spectroscopy of a ferroelectric thin film, exploring with different kernels and acquisition functions. This work shows an advancement towards human-AI collaborated automated experiments, steering optimization trajectories through human overpowering AI at the early stage when uncertainty is high and AI overpowering human at the later stage with rapid exploration towards optimal goal, following human-assessed multiple targets properties.
The plane-wave pseudopotential (PW-PP) formalism is widely used for the first-principles electronic structure calculation of extended periodic systems. The PW-PP approach has also been adapted for real-time time-dependent density functional theory (RT-TDDFT) to investigate time-dependent electronic dynamical phenomena. In this work, we detail recent advances in the PW-PP formalism for RT-TDDFT, particularly how maximally localized Wannier functions (MLWFs) are used to accelerate simulations using the exact exchange. We also discuss several related developments, including an anti-Hermitian correction for the time-dependent MLWFs (TD-MLWFs) when a time-dependent electric field is applied, the refinement procedure for TD-MLWFs, comparison of the velocity and length gauge approaches for applying an electric field, and elimination of long-range electrostatic interaction, as well as usage of a complex absorbing potential for modeling isolated systems when using the PW-PP formalism.