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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 253 records · Page 14

Scientific frontiers of agrivoltaic cropping systems

Agrivoltaic (AV) systems integrate agriculture with electricity conversion through photovoltaic (PV) modules. Compared with conventional ground-mounted PV systems, AV systems can reduce land-use competition and offer agronomic and economic advantages, such as more stable crop production and additional farm income. However, AV systems can decrease agricultural performance and are typically 20-90% costlier to install than conventional PV systems. Here, in this Review, we analyse the implementation of AV cropping systems to preserve agricultural activities and highlight challenges and barriers. The global electricity potential of AV systems is ~66-385 PWh annually, depending on PV technology and installation density, if deployed in the most suitable areas, without accounting for grid availability. Scaling up has been hindered by crop selection for shading conditions, decreased energy conversion per unit of land area and issues with social acceptance, landscape impact and environmental sustainability. These issues can be addressed by developments such as wavelength-selective PV; system configurations, such as optimizing module spacing to reduce shading; and operational methods, such as optimizing tracking strategies and integrating agricultural infrastructure. Cross-sector policies can support AV systems by addressing the needs of diverse stakeholders over shared land resources. Further development will require collaboration among the design, performance, deployment and systems research communities.

14 SOLAR ENERGY↗

Quantifying Risk in an Uncertain Future: The Evolution of Resource Adequacy

As our power grids transition toward a decarbonized energy mix, ensuring reliability and provision of grid services remains paramount. The power system has always been heavily influenced by the weather - extreme temperatures determine the timing of peak demand, winter cold snaps can limit natural gas supply, gas turbine reliability and output are affected by ambient conditions, and hydro output varies seasonally and annually. However, as the grid increasingly relies on variable renewable energy (VRE), like wind and solar, the attention to reliability and weather conditions is increasingly important. The implications of changing reliability are large. The Electric Reliability Council of Texas (ERCOT) rolling blackouts from earlier this year impacted millions of people across the state and could be seen from space (Figure 1).

hydraulic turbines↗

Computed Tomography Scanning and Geophysical Measurements of the CarbonSAFE Seal Integrity Wells in the Illinois Basin

The U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) researchers in Morgantown, West Virginia, utilized computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) to evaluate the integrity of three cores (Geophysical Monitor #2 (GM2), Verification Well #1 (VW #1), and Wabash #1 for the Illinois Basin Carbon Storage Assurance Facility Enterprise (CarbonSAFE) efforts. This work was carried out in collaboration with the Illinois State Geological Survey (ISGS) as part of their efforts to analyze cores from two field locations, including the Illinois Basin-Decatur Project (IBDP) and second stage Illinois Industrial Carbon Capture and Storage (IL-ICCS) sites at Decatur, Illinois, and the Wabash CarbonSAFE project at the Wabash Valley Resources Integrated Gasification Combined Cycle plant in Terre Haut, Indiana. The results of this study are presented in several formats and are available online on the Energy Data eXchange (EDX). The rock characterization was conducted using non-destructive techniques, allowing for future analysis of the cores. While the equipment used did not provide direct visualization of shale pore space, it allowed for detection of fractures and discontinuities. Low resolution CT imagery with the NETL medical CT scanner was performed on the entire core. Qualitative analysis of the medical CT images, coupled with x-ray fluorescence (XRF), P-wave, and magnetic susceptibility measurements from the MSCL were utilized to identify areas of interest for further study as well as fractured zones. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provided a multi-scale analysis of this core and provided both a macro and micro description of the core that is relevant for many subsurface energy-related examinations traditionally performed at NETL.

58 GEOSCIENCES↗

Rare Earth Elements (REE) and Critical Minerals (CM) in Middle Pennsylvanian-Age Coals and Associated Sediments in the Central Appalachian Basin, Eastern U.S.A.

The Central Appalachian Basin (CAB) of Kentucky, Tennessee, West Virginia and Virginia has a long history of coal mining and oil and gas extraction that has empowered the regional and national economies, the development of infrastructure, and a highly trained energy resources work force. As our societal demands for advanced technologies have rapidly increased in recent years, coal-related materials are viewed as an important new unconventional domestic source of critical minerals (CM) that are required for telecommunications, aerospace and transportation industries, electronics, the transition to low-carbon emissions energy production, and many consumer products. Coal-related materials encompass coal, associated sediments, coal mining waste materials, produced waters, and ash residues from coal-fired power plants. An important objective of the Evolve Central Appalachia Project (Evolve CAPP), sponsored by the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL) is to assess the quantity and distribution of CM resources in the CAB region. The rare earth elements (REE) are considered highest priority, although other important CM such as niobium, gallium, and zirconium are known to occur in the Middle Pennsylvanian-age coals and sediments. Working with coal industry partners who provided access to drill cores, coal-related sediments and waste materials, over 600 samples have been collected for laboratory analysis, and over 730 materials have been scanned using portable x-ray fluorescence (pXRF) equipment. The application of pXRF provides the means for real-time semiquantitative analysis of CM content at very close spacings (typically 2-3 inch intervals) along drill core and in-situ channel samples that span the roof, coal seam, and floor rock. The comparison of pXRF geochemical data with laboratory results, geologic data, and downhole spectral gamma logs can provide high resolution input to lithologic and depositional models for future CM resource evaluations. The preliminary findings show that pXRF is capable of accurately measuring low concentrations of many of the CM with a high level of confidence (Ba, Cr, Ga, K, Nb, Rb, Sr, Th, Y), whereas for others (La, Ce, Co, Mn, Nd, Ni, Sc, Ti, V) the detection limits are very high or spectral interferences increase the uncertainty. Notably, the mean abundances of Y (34 ppm), La (86 ppm), Ga (40 ppm), and V (146 ppm) in coal underclays in the CAB region are up to 7X enriched compared with the overlying coal. These values also exceed the reported concentrations in published reference materials for upper continental crustal rocks (Rudnick and Gao, 2003), North American Shale Composite (Gromet et al., 1984), and North American coal (Finkelman, 1993). The pXRF data are in part verified by laboratory results that indicate the mean Y abundance (36 ppm) is highly correlated (R2 = 0.807) with total REE (ΣREE). The correlation is even higher (R2 = 0.957) with heavy REE (ΣHREE). Applying these correlations to the pXRF data for the coal underclays, the mean estimated values for ΣREE+Y and ΣHREE+Y are 270 ppm and 58 ppm, respectively. Although these average values are not considered high, the range of Y measured by pXRF in the coal underclays extended as high as 114 ppm, which would suggest ΣREE+Y equal to 847 ppm. The mean abundances of Zr (192 ppm) and Th (21 ppm) in coal underclays are also enriched compared with the overlying coal and these results likely reflect the presence of resistant detrital heavy minerals such as monazite, xenotime, and zircon in the underclay matrix. Several of the profiled coal seams and associated wall rocks contained thin volcanic ash layers up to 4-5 inches in thickness. The extent to which these ash fall layers provided a source for CM under the paleoenvironmental conditions that resulted in coal deposits in the CAB remains to be fully studied. Continuing investigations in the Evolve CAPP study area will include laboratory determinations of mineralogic and clay compositions, and evaluations of CM geochemical mobility in the coal and coal underclays.

Lassetter, Billy↗

Ocean Energy: Markets - Currency - Impact. Dimension of & Choices in the Technology Development Space: Preprint

This paper presents considerations of the employment of ocean wave energy to support different energy demand side applications. The key aspect in these considerations is the wave energy supported achievable positive impact and associated tangible contribution in service of common societal good and of the natural commons. The level of impact that can be delivered is dependent on both, the level of contribution of the supported energy use application, and the compatibility and unique suitability of the wave energy resource and its characteristics with the needs of the application. Thus, a variety of ocean wave energy markets, the key value indicators or "currency' in which these markets trade the value delivered and the achievable positive impact, are reflected upon. Ocean wave energy supported acquisition of high quality ocean system data across a wide spectrum of system properties is identified as a highly impactful application enabling and/or improving a comprehensive range of impactful ocean system activities. The technology development process towards these markets and desired impacts requires relevant technology development progress guidance and metrics. Going beyond technology readiness levels and technology performance levels, the notion of further technology development progress scales towards high impact and high contribution are proposed. These scales and the associated technology properties can be regarded as additional technology development dimensions to span-up the technology development space in which desired system capability and functional requirement choices and subsequent ideation, innovation, research and technology development decisions can and are to be made.

data market↗

Active deep kernel learning of molecular properties from structural embeddings

As vast databases of chemical identities become increasingly available, the challenge shifts to how we effectively explore and leverage these resources to study molecular properties. This paper presents an active learning approach for molecular discovery using deep kernel learning (DKL), demonstrated on the QM9 dataset. DKL links structural embeddings directly to properties, creating organized latent spaces that prioritize relevant property information. By iteratively recalculating embedding vectors in alignment with target properties, DKL uncovers concentrated maxima representing key molecular properties and reveals unexplored regions with potential for innovation. This approach underscores DKL’s potential in advancing molecular research and discovery.

Artificial neural networks↗

Integrating ytopt and libEnsemble to autotune OpenMC

Ytopt is a Python machine-learning-based autotuning software package developed within the ECP PROTEAS-TUNE project. The ytopt software adopts an asynchronous search framework that consists of sampling a small number of input parameter configurations and progressively fitting a surrogate model over the input-output space until exhausting the user-defined maximum number of evaluations or the wall-clock time. libEnsemble is a Python toolkit for coordinating workflows of asynchronous and dynamic ensembles of calculations across massively parallel resources developed within the ECP PETSc/TAO project. libEnsemble helps users take advantage of massively parallel resources to solve design, decision, and inference problems and expands the class of problems that can benefit from increased parallelism. In this paper we present our methodology and framework to integrate ytopt and libEnsemble to take advantage of massively parallel resources to accelerate the autotuning process. Specifically, we focus on using the proposed framework to autotune the ECP ExaSMR application OpenMC, an open source Monte Carlo particle transport code. OpenMC has seven tunable parameters some of which have large ranges such as the number of particles in-flight, which is in the range of 100,000 to 8 million, with its default setting of 1 million. Setting the proper combination of these parameter values to achieve the best performance is extremely time-consuming. Therefore, we apply the proposed framework to autotune the MPI/OpenMP offload version of OpenMC based on a user-defined metric such as the figure of merit (FoM) (particles/s) or energy efficiency energy-delay product (EDP) on Crusher at Oak Ridge Leadership Computing Facility. In conclusion, the experimental results show that we achieve the improvement up to 29.49% in FoM and up to 30.44% in EDP.

Autotuning↗

A Review of Distributed Wind Interconnection Technology and Standards

The objectives of this report are to discuss the uniqueness of power converters in distributed wind (DW), identify challenges in complying with existing standards, prioritize technological innovations to facilitate interconnection of DW energy systems, and, where necessary, propose potential clarifications or revisions to standards. This report evaluates IEEE 1547-2018, IEEE 1547.1-2020, and UL 1741 SB standards and their implications for DW. A standards review and interviews of DW industry stakeholders were conducted to identify challenges in the application of current standards to DW. The study concludes with a combination of recommendations of pathways towards facilitating DW product commercialization and DW interconnection, which draws on participation from multiple stakeholders in the space. These solutions can continue to be explored to improve DW standards compliance, improve the applicability of the standards to DW, reduce certification testing barriers, and ensure the safe and reliable operation of DW energy resources and electric power systems.

17 WIND ENERGY↗

Compactly‐Supported Nonstationary Kernels for Computing Exact Gaussian Processes on Big Data

The Gaussian process (GP) is a widely used method for analyzing large-scale data sets, including spatio-temporal measurements of nonlinear processes that are now commonplace in the environmental sciences. Traditional implementations of GPs involve stationary kernels (also termed covariance functions) that limit their flexibility, and exact methods for inference that prevent application to data sets with more than about 10,000 points. Modern approaches to address stationarity assumptions generally fail to accommodate large data sets, while all attempts to address scalability focus on approximating the Gaussian likelihood, which can involve subjectivity and lead to inaccuracies. In this work, we explicitly derive an alternative kernel that can discover and encode both sparsity and nonstationarity. We embed the kernel within a fully Bayesian GP model and leverage high-performance computing resources to enable the analysis of massive data sets. We demonstrate the favorable performance of our novel kernel relative to existing exact and approximate GP methods across a variety of synthetic data examples. Furthermore, we conduct space–time prediction based on more than 1 million measurements of daily maximum temperature and verify that our results outperform state-of-the-art methods in the Earth sciences. More broadly, having access to exact GPs that use ultra-scalable, sparsity-discovering, nonstationary kernels allows GP methods to truly compete with a wide variety of machine learning methods.

Gaussian processes↗

Adaptive Computing for Scale-Up Problems

Adaptive Computing is an application-agnostic outer loop framework to strategically deploy simulations and experiments to guide decision making for scale-up analysis. Resources are allocated over successive batches, which makes the allocation adaptive to some objective such as optimization or model training. The framework enables the characterization and management of uncertainties associated with predictive models of complex systems when scale-up questions lead to significant model extrapolation. A key advancement of this framework is its integration of multi-fidelity surrogate modeling, uncertainty management, and automated orchestration of various computing and experimentation resources into a single integrated software package. This enables efficient multi-fidelity modeling across multiple computing resources by incorporating real-world constraints such as relative queue times and throughput on individual machines into the multi-fidelity sampling decision. We discuss applications of this framework to problems in the renewable energy space, including biofuels production, material synthesis, perovskite crystal growth, and building electrical loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Quantum Approximate Optimization Algorithm on Different Qubit Systems

Solving optimization problems is critical across many research domains, but the high dimensionality of parameter spaces often poses significant challenges. The Quantum Approximate Optimization Algorithm (QAOA) has emerged as a promising approach for accelerating optimization in the Noisy Intermediate-Scale Quantum (NISQ) era by leveraging both classical and quantum computational resources. However, its performance can vary depending on the underlying quantum hardware architecture. In this work, we evaluate the performance of QAOA on different quantum hardware platforms, specifically, superconducting transmon qubits and trapped-ion qubits, targetting real-world optimization problems formulated as fully connected Quadratic Unconstrained Binary Optimization (QUBO) instances. We evaluate both the solution quality and time-to-solution using dense QUBO matrices. Furthermore, we show that large-scale problems, such as a 100-bit QUBO instance, can be effectively tackled by integrating quantum computing with high-performance computing (HPC) resources. This study provides practical insights into the strengths and limitations of different qubit technologies and advances the application of quantum computing in solving real-world optimization problems.

Kim, Seongmin [ORNL] (ORCID:0000000159063004)↗

A section 110 evaluation of the huron king test chamber, area 3, nevada national security site, nye county, nevada

The U.S. Department of Energy, National Nuclear Security Administration Nevada Field Office tasked Desert Research Institute (DRI) with the identification and evaluation of the Huron King Test Chamber as part of their cultural resources program obligations under Section 110 of the National Historic Preservation Act. The Huron King nuclear test was a vertical line-of-sight weapons effects test that took place in Area 3 on June 24, 1980. Unique to this event was a specially designed aboveground test chamber that held a model defense communications satellite in a vacuum tank meant to replicate the space environment. Sponsored by the Defense Nuclear Agency, the purpose of the experiment was to understand the response of the satellite and its materials and equipment to an electromagnetic pulse and attendant radiation. Between July and August 2022, DRI conducted an archival review on the Huron King experiment and its associated test chamber. Subsequently, pedestrian fieldwork was undertaken at the Huron King Test Chamber by DRI on September 29, 2022. During fieldwork, the outside of the test chamber was documented using a Nevada State Historic Preservation Office Architectural Resource Assessment form. This effort included verifying the substructures that compose the test chamber as determined by the archival review, as well as obtaining a detailed photographic recordation of the exterior and assessing its current condition. Notably, the site where the Huron King test took place has been abandoned and almost entirely naturalized. All of the portable instrumentation trailers, communications and data cabling, and winch systems used to retract the test chamber following the detonation were removed after completion of the experiment in 1980. Only the subsidence crater and the test chamber remain as physical evidence of this experiment. Based on these findings, DRI recommends that the Huron King Test Chamber is eligible for listing in the National Register of Historic Places (NRHP) at the local level under Significance Criteria A and C and that it meets Criteria Consideration G for properties less than 50 years old.

54 ENVIRONMENTAL SCIENCES↗

Parameter Reduction of Composite Load Model Using Active Subspace Method

Over the past decades, the increasing penetration of distributed energy resources (DERs) has dramatically changed the power load composition in the distribution networks. The traditional static and dynamic load models can hardly capture the dynamic behavior of modern loads especially for fault-induced delayed voltage recovery (FIDVR) events. Thus, a more comprehensive composite load model with combination of static load, different types of induction motors, single-phase A/C motor, electronic load and DERs has been proposed by Western Electricity Coordinating Council (WECC). However, due to the large number of parameters and model complexity, the WECC composite load model (WECC CMLD) raises new challenges to power system studies. To overcome these challenges, in this paper, a cutting-edge parameter reduction (PR) approach for WECC CMLD based on active subspace method (ASM) is proposed. Firstly, the WECC CMLD is parameterized in a discrete-time manner for the application of the proposed method. Then, parameter sensitivities are calculated by discovering the active subspace, which is a lower-dimensional linear subspace of the parameter space of WECC CMLD in which the dynamic response is most sensitive. The interdependency among parameters can be taken into consideration by our approach. Finally, the numerical experiments validate the effectiveness and advantages of the proposed approach for WECC CMLD model.

active subspace↗

Status and future plans for C 3 R&D

C 3 is an opportunity to realize an e + e - collider for the study of the Higgs boson at √s = 250 GeV, with a well defined upgrade path to 550 GeV while staying on the same short facility footprint. C 3 is based on a fundamentally new approach to normal conducting linear accelerators that achieves both high gradient and high efficiency at relatively low cost. Given the advanced state of linear collider designs, the key system that requires technical maturation for C 3 is the main linac. This paper presents the staged approach towards a facility to demonstrate C 3 technology with both Direct (source and main linac) and Parallel (beam delivery, damping ring, ancillary component) R&D. The primary goal of the C 3 Demonstration R&D Plan is to reduce technical and cost risk by building and operating the key components of C 3 at an adequate scale. This R&D plan starts with the engineering design, and demonstration of one cryomodule and will culminate in the construction of a 3 cryomodule linac with pre-production prototypes. This R&D program would also demonstrate the linac rf fundamentals including achievable gradient and gradient stability over a full electron bunch train and breakdown rates. It will also investigate beam dynamics including energy spread, wakefields, and emittance growth. This work will be critical to confirm the suitability of the C 3 beam parameters for the physics reach and detector performance in preparation for a Conceptual Design Report (CDR), as well as for follow-on technology development and industrialization. The C 3 Demonstration R&D Plan will open up significant new scientific and technical opportunities based on development of high-gradient and high-efficiency accelerator technology. It will push this technology to operate both at the GeV scale and mature the technology to be reliable and provide high-brightness electron beams. The timeline for progressing with C 3 technology development will be governed by practical limitations on both the technical progress and resource availability. It consists of four stages: Stage 0) Ongoing fundamental R&D on structure prototypes, damping and vibrations. Stage 1) Advancing the engineering maturity of the design and developing start-to-end simulations including space-charge and wakefield effects. This stage will include testing of strucutres operating at cryogenic temperatures. Beam tests would be performed with high beam current to test full beam loading. Stage 2) Production and testing of the first cryomodule at cryogenic temperatures. This would provide sufficient experimental data to compile a CDR and it is anticipated for Stage 2 to last 3 years and to culminate with the transport of photo-electrons through the first cryomodule. Stage 3) Updates to the engineering design of the cryomodules, production of the second and third cryomodule and their installation. Lower charge and lower emittance beams will be used to investigate emittance growth. The successful full demonstration of the 3 cryomodules to deliver up to a 3 GeV beam and achieve the C 3 five gradient will allow a comprehensive and robust evaluation of the technical design of C 3 as well as mitigate technical, schedule, and cost risks required to proceed with a Technical Design Report (TDR).

radiation hardened magnets↗

Critical Design Elements for an On-Site Mercury Concentration and Holding Facility - 20175

Administrative changes and funding issues have delayed the Department of Energy (DOE) from establishing and commissioning a National Repository for mercury as required under the Mercury Export Ban Act (MEBA) of 2008. In the interim, a few hazardous waste Treatment, Storage, and Disposal Facilities (TSDFs) have been authorized to accept mercury classified as a hazardous waste as under Subtitle C of the Resource Conservation and Recovery Act (RCRA). Waste generators are charged (either by weight or by volume) for the waste they manifest to these TSDFs. In many cases, mercury and mercury compounds have chemically sorbed to (or physically lodged into) the interstitial spaces of a substrate material. This almost always causes the amount of waste generated to be unnecessarily large, due to the extra volume (or weight) of the accompanying, non-mercury materials. Depending on a multitude of factors, it could be financially beneficial for waste generators to take greater control of their mercury affairs by separating these substrate materials from the mercury and mercury compounds that have become associated with them. Building and operating an on-site mercury Concentration and Holding Facility (CHF) could help relieve a waste generator's overall cost burden. The purpose of such CHFs is not to treat or dispose of mercury, but to recover and concentrate mercury from bulky mercury-laden materials to the extent that the host substrate to which the mercury may have previously been sorbed could pass a Toxicity Characteristic Leaching Procedure (TCLP) test and either be disposed of at a conventional landfill, or be disposed of at a hazardous waste landfill, but absent additional restrictions specifically for mercury. A CHF represents a way for waste generators to save money by separating mercury from common host materials, concentrating it, and then safely storing it until transportation to an authorized TSDF takes place This paper focuses on the critical design elements waste generators should consider when designing and operating a mercury CHF. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Visual Tool for Assessing Stability of DER Configurations on Three-Phase Radial Networks

Here, we present a method and tool for evaluating the placement of Distributed Energy Resources (DER) on distribution circuits in order to control voltages and power flows. Our previous work described Phasor-Based Control (PBC), a novel control framework where DERs inject real and reactive power to track voltage magnitude and phase angle targets. Here, we employ linearized power flow equations and integral controllers to develop a linear state space model for PBC acting on a three-phase unbalanced network. We use this model to evaluate whether a given inverter-based DER configuration admits a stable set of controller gains, which cannot be done by analyzing controllability nor by using the Lyapunov equation. Instead, we sample over a parameter space to identify a stable set of controller gains. Our stability analysis requires only a line impedance model and does not entail simulating the system or solving an optimization problem. We incorporate this assessment into a publicly available visualization tool and demonstrate three processes for evaluating many control configurations on the IEEE 123-node test feeder (123NF).

24 POWER TRANSMISSION AND DISTRIBUTION↗

Pathways for Nucleation and Growth in Confined Spaces and at Interfaces

Mineral crystallization is central to myriad natural processes from the formation of snowflakes to stalagmites, but the molecular-scale mechanisms are often far more complex than models reflect. Feedbacks between the hydro-, bio-, and geo-spheres drive complex crystallization processes that challenge our ability to observe and quantify them, motivating an expansion of crystallization theories. Here, in this article, we discuss how the driving forces and timescales of nucleation are influenced by factors ranging from simple geometric confinement to distinct interfacial solution structures involving solvent organization, electrical double layers, and surface charging effects. Taken together, these ubiquitous natural phenomena can preserve metastable intermediates, drive precipitation of undersaturated phases, and modulate crystallization in time and space.

biosphere↗

A Fast and Accurate Transient Stability Assessment Method Based on Deep Learning: WECC Case Study

Transient stability is one of the critical aspects of power system stability assessment. The increasing integration of inverter-based resources and the retirement of conventional synchronous generators result in the decreasing system inertia and growing complexity of system operating conditions. Using a few selected typical operating conditions cannot guarantee system transient stability in all operating conditions, and the time-domain simulation of all operating conditions requires tremendous time and is often infeasible. This paper proposes a more efficient transient stability assessment method based on deep learning. The binary search method is used to determine the critical clearing time (CCT) in creating training databased by time-domain simulation. This method is fast and accurate with 1 ms resolution. The buses whose CCTs are lower than 200 ms are considered critical buses. Buses close to each other are grouped based on their mutual admittance matrix to reduce the search space of the critical buses. This paper also proposes the generator feature normalization based on the physical model. Case study on the reduced 240-bus WECC system model demonstrates that the proposed method can predict CCT accurately and efficiently.

critical clearing time↗