Search NASA⌕ Search

SEARCH · Search NASA

Results for “Large load”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Greggd

greg(g)d - Global runtime for eBPF-enabled gathering (w/ gumption) daemon Recently the linux kernel has added support for low-level kernel monitoring and profiling through a in-kernel virtual machine. The tooling around these new features (the extended Berkley Packet Filter or eBPF for short) is not mature and is difficult to use. Benefits from eBPF are especially hard to realize while trying to do large scale deployments and integrate with existing metric analysis stacks. A tool was needed to enable loading and collecting data from eBPF programs on large scale HPC systems. Given the problems above it was obvious we needed some wrapper program to compile, load, and collect data from eBPF programs running in the kernel. This tool needed to be lightweight without a heavy set of dependencies, relatively stable between different kernel versions, and integrate nicely with existing widely used metric collection tools. We wrote a program that wraps the eBPF tooling and sends data to our metric gathering tool. eBPF programs are either compiled using the host compiler stack, or loaded in the kernel directly from an object file. These programs are then attached to the system calls that we want to profile. Whenever these system calls are run, the eBPF program collects information of interest and writes that to memory. Our wrapper program polls these memory locations, reads and formats the data, then sends the information to a local unix socket. Our other monitoring tools are configured to read from that socket and send it to the rest of our metric monitoring stack for analysis.

Voss, Joseph [Oak Ridge National Lab. (ORNL), Oak ↗
DOE OSTI2022

Sodium-ion Battery

Room temperature rechargeable sodium-ion batteries (NIBs) are one of the most promising candidates for large-scale energy storage and load leveling of renewable energy sources due to the abundance, low cost of Na resources, and their relatively high energy density. NIBs are primarily based on intercalation chemistry and are similar to Lithium-ion batteries (LIB). The rich knowledge gained in LIBs for the past 4 decades have accelerated the discovery and development of high energy density NIBs cathode and anode materials. The use of sustainable Na, Al current collector, and Mn and Fe based cathode materials is expected to stabilize the cost and demand for Li, Co, Ni and Cu.

Omenya, Fredrick O.↗
DOE OSTI2020

Parallel three-dimensional simulations of quasi-static elastoplastic solids

Hypo-elastoplasticity is a flexible framework for modeling the mechanics of many hard materials under small elastic deformation and large plastic deformation. Under typical loading rates, most laboratory tests of these materials happen in the quasi-static limit, but there are few existing numerical methods tailor-made for this physical regime. Here, we extend to three dimensions a recent projection method for simulating quasi-static hypo-elastoplastic materials. The method is based on a mathematical correspondence to the incompressible Navier–Stokes equations, where the projection method of Chorin (1968) is an established numerical technique. We develop and utilize a three-dimensional parallel geometric multigrid solver employed to solve a linear system for the quasi-static projection. Our method is tested through simulation of three-dimensional shear band nucleation and growth, a precursor to failure in many materials. As an example system, we employ a physical model of a bulk metallic glass based on the shear transformation zone theory, but the method can be applied to any elastoplasticity model. We consider several examples of three-dimensional shear banding, and examine shear band formation in physically realistic materials with heterogeneous initial conditions under both simple shear deformation and boundary conditions inspired by friction welding.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Topological structure enhanced nanostructure of high temperature polymer exhibiting more than ten times enhancement of dipolar response

Nanofillers in polymer composites will induce interface regions in the polymer with non-uniform nanostructures which can be approximated as multilayer shells surrounding nanofillers. This paper studies topological nanostructures in polymers that interface with one-dimensional (1-D) and zero-dimensional (0-D) nanofillers. This new class of dielectric polymer nanocomposites involves nanofillers at ultra-low volume loading (< 1 vol percent) that generate large dielectric enhancement. The results show that the dipolar response of polyetherimide, a high temperature dielectric polymer, is increased by more than ten times with ultra-low (0.75 vol %) loading of 1-D nanofillers. The results reveal that 1-D nanofillers induce cylindrical shell-topology in the polymer matrix which is more effective in enhancing the high dielectric constant interfacial region than the spherical shell-topology generated by 0-D fillers. Furthermore, the cylindrical shells generated by 1-D fillers provide much higher dielectric enhancement over a broader interfacial region in the polymer matrix, as compared to the spherical shells induced by 0-D nanofillers.

42 ENGINEERING↗
DOE OSTI2025

PySIDT: Subgraph Isomorphic Decision Trees for Molecular Property Prediction

Accurate molecular property prediction is important across all fields of chemistry. Deep neural networks (DNNs) have become increasingly popular due to their ability to train automatically, avoiding the incredibly tedious process of constructing and extending traditional property estimation schemes. However, DNNs require large amounts of training data, are challenging to interpret, require large amounts of memory to load even during inference, and have severe difficulties incorporating qualitative chemical knowledge, which are often desired for molecular property prediction tasks. Here, in this study, we present PySIDT (https://github.com/zadorlab/PySIDT), a software for training and running inference on Subgraph Isomorphic Decision Trees (SIDTs). SIDTs are graph-based decision trees made of nodes associated with molecular substructures. Inference is done by descending target molecular structures down the decision tree to nodes with matching subgraph isomorphic substructures and making predictions based on the final (most specific) nodes matched. SIDTs scale down well to dataset sizes much smaller than is feasible for DNNs. As trees of molecular substructures, SIDTs are inherently readable and easy to visualize, making them easy to analyze. They are also straightforward to extend and retrain, facilitate uncertainty estimation, and enable easy integration of expert knowledge. We demonstrate the SIDT approach discussing its application to a diverse range of molecular prediction tasks: rate coefficient estimation, diffusion coefficient estimation, thermochemistry estimation, transition state bond stretch prediction, p K a prediction, stability of molecular structures, stability of surface structures, and prediction of surface lateral interaction energetics. Additionally, we demonstrate the power of the SIDT algorithms in two direct learning curve vanilla comparisons with the popular DNN-based software Chemprop and the popular gradient boosted trees-based software XGBoost on enthalpy of formation and rate coefficient prediction tasks. In particular, in the enthalpy of formation case, vanilla PySIDT is able to outperform vanilla Chemprop and XGBoost across the full range of training/validation set sizes out to 11,560 data points.

Johnson, Matthew Sean [Sandia National Laboratorie↗
DOE OSTI2026

Phase instability-coupled fracture behavior in garnet LLZO solid electrolytes: a machine learning-enabled atomistic study

Fracture in the garnet-type solid electrolyte Li 7 La 3 Zr 2 O 12 (LLZO) poses a critical threat to both the performance and safety of solid-state batteries. To unravel the coupled chemomechanical processes that govern fracture in LLZO under external loading, we carry out large-scale molecular-dynamics simulations with a validated machine-learning force field. Our results demonstrate that triaxial stresses at crack flanks trigger a localized cubic-to-tetragonal phase transformation, which is accompanied by Li-ion rearrangement. The emergent tetragonal domains feature lattice contraction normal to the fracture plane, imposing coherent misfit strains that provide an additional driving force for further crack propagation. Crucially, introducing Li deficiencies stabilizes the cubic phase, postponing the phase transition and thereby delaying fracture initiation. These findings highlight the role of intrinsic phase instability in dictating LLZO's fracture resistance and its critical connection to local Li concentration. This chemomechanical coupling points toward targeted strategies to enhance the mechanical robustness of garnet electrolytes, including tuning Li content, ensuring dopant homogeneity, and refining processing protocols.

Materials science↗
DOE OSTI2024

Dynamic response of additively manufactured Ti–5Al–5V–5Mo–3Cr as a function of heat treatment

Both shock and shockless compression experiments were performed on laser powder bed fusion (LPBF) Ti–5Al–5V–5Mo–3Cr (Ti-5553) to peak compressive stresses near 15 GPa. Experiments were performed on the as-built material, containing a purely β (body centered cubic) microstructure, and two differing heat treatments resulting in a dual phase α (hexagonal close packed) and β microstructure. The Hugoniot, Hugoniot elastic limit (HEL), and spallation strength were measured and compared to wrought Ti-6Al-4V (Ti-64). The results indicate the LPBF Ti-5553 Hugoniot response is similar between heat treatments and to Ti-64. The HEL stress observed in the LPBF Ti-5553 was considerably higher than Ti-64, with the as-built, fully β alloy exhibiting the largest values. The spallation strength of the LPBF Ti-5553 was also similar to Ti-64. Clear evidence of initial porosity serving as initiation sites for spallation damage was observed when comparing computed tomography measurements before and after loading. Post-mortem scanning electron microscopy images of the recovered spallation samples showed no evidence of retained phase changes near the spall plane. The spall plane was found to have kinks aligned with the loading direction near areas with large concentrations of twin-like, crystallographic defects in the as-built condition. For the heat-treated samples, the concentrations of twin-like, crystallographic defects were absent, and no preference for failure at the interface between the α and β phases was observed.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Dynamic Adaptive Relaying for Distribution Grids with High Inverter-Based Generation

The penetration of distributed energy resources (DERs) in distribution systems is rapidly increasing. This can lead to large variations in the operating load and the fault current seen by a relay, which can impact the reliability of overcurrent protection. Adaptive overcurrent relaying (AOCR) can address this concern by enabling the relay to adjust its pickup settings based on the system operating conditions. This paper presents a novel dynamic AOCR approach that allows the relays to locally estimate the pickup settings and dynamically modify them. The approach is based on a two-stage estimation algorithm that uses local measurements and system information to estimate the worst-case fault current and the relay pickup settings. The relay pickup settings are then dynamically modified based on the estimated fault current. The performance of the proposed approach is evaluated on multiple configurations of the EPRI J1 feeder and the IEEE 13-bus system. The results show that the proposed approach can effectively improve the reliability of overcurrent protection in distribution systems with DERs.

adaptive overcurrent protection↗
DOE OSTI2023

Control Co-Design of Wind Turbines

Wind energy is recognized worldwide as cost-effective and environmentally friendly, and it is among the fastest-growing sources of electrical energy. To further decrease the cost of wind energy, wind turbines are being designed at ever-larger scales. To expand the deployment of wind energy, wind turbines are also being designed on floating platforms for placement in deep-water locations offshore. Both larger-scale and floating wind turbines pose challenges because of their greater structural loads and deflections. Complex, large-scale systems such as modern wind turbines increasingly require a control co-design approach, whereby the system design and control design are performed in a more integrated fashion. This article reviews recent developments in control co-design of wind turbines. We provide an overview of wind turbine design objectives and constraints, issues in the design of key wind turbine components, modeling of the wind turbine and environment, and controller coupling issues. Wind turbine control functions and the integration of control design in co-design are detailed with a focus on co-design compatible control approaches.

17 WIND ENERGY↗
DOE OSTI2022

GLUE Code: A framework handling communication and interfaces between scales

Many scientific applications are inherently multiscale in nature. Such complex physical phenomena often require simultaneous execution and coordination of simulations spanning multiple time and length scales. This is possible by combining expensive small-scale simulations (such as molecular dynamics simulations) with larger scale simulations (such continuum limit/hydro solvers) to allow for considerably larger systems using task and data parallelism. However, the granularity of the tasks can be very large and often leads to load imbalance. Traditionally, we use approximations to streamline the computation of the more costly interactions and this introduces trade-offs between simulation cost and accuracy. In recent years, the available computational power and the advances in machine learning have made computing these scale-bridging interactions and multiscale simulations more feasible. One driving application has been plasma modeling in inertial confinement fusion (ICF), which is fundamentally multiscale in nature. This requires deep understanding of how to extrapolate microscopic information into macroscopically relevant scales. For example, in ICF one needs an accurate understanding of the connection between experimental observables and the underlying microphysics. The properties of the larger scales are often affected by the microscale behavior incorporated usually into the equations of state and ionic and electronic transport coefficients (Liboff, 1959; Rinderknecht et al., 2014; Rosenberg et al., 2015; Ross et al., 2017). Instead of incorporating this information using reliable molecular dynamics (MD) simulations, one often needs to use theoretical models, due to the inability of MD to reach engineering scales (Glosli et al., 2007; Marinak et al., 1998). One approach to resolve this issue is by coupling two MD simulations of different scales via force interpolation, e.g., the AdResS method (Krekeler et al., 2018; Nagarajan et al., 2013). Another approach, which we will pursue in the scope of this work, is by enabling scale bridging between MD simulations and meso/macro-scale models through the development and support of application programming interfaces that these different applications can interact through.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

DRDMannTurb: A Python package for scalable, data-driven synthetic turbulence

Synthetic turbulence models (STMs) are used in wind engineering to generate realistic flow fields and are employed as inputs to industrial wind simulations. Examples include prescribing inlet conditions in large eddy simulations that model loads on wind turbines and tall buildings. We are interested in STMs capable of generating fluctuations based on prescribed second-moment statistics since such models can simulate environmental conditions that closely resemble on-site observations. To this end, the widely used Mann model (see Mann, 1994, 1998) is the inspiration for DRDMannTurb. The Mann model is described by three physical parameters: a magnitude parameter influencing the global variance of the wind field and corresponding to the Kolmogorov constant multiplied by the rate of viscous dissipation of the turbulent kinetic energy to the two-thirds, αϵ 2/3 , a turbulence length scale parameter L, and a nondimensional parameter Γ related to the lifetime of the eddies. A number of studies, as well as international standards (e.g., those by the International Electrotechnical Commission (IEC)), include recommended values for these three parameters with the goal of standardizing wind simulations according to observed energy spectra. Yet, having only three parameters, the Mann model faces limitations in accurately representing the diversity of observable spectra. This Python package enables users to extend the Mann model and more accurately fit field measurements through flexible neural network models of the eddy lifetime function. Following Keith et al. (2021), we refer to this class of models as Deep Rapid Distortion (DRD) models. DRDMannTurb also includes a general module implementing an efficient method for synthetic turbulence generation based on a domain decomposition technique. This technique is also described in Keith et al. (2021).

17 WIND ENERGY↗
DOE OSTI2024

Cyber-Physical Simulation of an Innovative Solid Oxide Electrolysis Cell - Gas Turbine (SOEC-GT) Hybrid Energy System

To produce green hydrogen at scale and at low cost, the solid oxide electrolysis cell (SOEC) systems would be tied to renewable power sources (mainly solar and wind), leveraging zero-carbon electricity at low prices and even nearly free during overgeneration scenarios. However, due to the intermittency of renewable power generation, the SOEC system is subjected to rapid load transitions that occur not only in diurnal cycles but also in short timeframes (e.g., sub-minute). This can result in fast degradation and thus greatly reduce the SOEC’s lifetime. Our team at the National Energy Technology Laboratory has demonstrated that the anode air flow can have a crucial role in SOEC thermal management. Typically, a higher air flow rate can help to mitigate the local temperature gradient distortion during rapid load transitions. To move a large amount of air, the gas turbine (GT; i.e., compressor-turbine-generator set) has been regarded as the most mature and efficient technology. In this presentation, we show the configuration and preliminary results of an innovative SOEC-GT hybrid energy system in a cyber-physical simulation (CPS) approach.

Zhang, Biao↗
DOE OSTI2021

Sequence-Defined Nanotubes Assembled from IR780-Conjugated Peptoids for Chemophototherapy of Malignant Glioma

Near-infrared (NIR) laser-induced phototherapy through NIR agents has demonstrated the great potential for cancer therapy. However, insufficient tumor killing due to the nonuniform heat or cytotoxic singlet oxygen ( 1 O 2 ) distribution over tumors from phototherapy results in tumor recurrence and inferior outcomes. To achieve high tumor killing efficacy, one of the solutions is to employ the combinational treatment of phototherapy with other modalities, especially with chemotherapeutic agents. In this paper, a simple and effective multimodal therapeutic system was designed via combining chemotherapy, photothermal therapy (PTT), and photodynamic therapy (PDT) to achieve the polytherapy of malignant glioma which is one of the most aggressive tumors in the brain. IR-780 (IR780) dye-labeled tube-forming peptoids (PepIR) were synthesized and self-assembled into crystalline nanotubes (PepIR nanotubes). These PepIR nanotubes showed an excellent efficacy for PDT/PTT because the IR780 photosensitizers were effectively packed and separated from each other within crystalline nanotubes by tuning IR780 density; thus, a self-quenching of these IR780 molecules was significantly reduced. Moreover, the efficient DOX loading achieved due to the nanotube large surface area contributed to an efficient and synergistic chemotherapy against glioma cells. Given the unique properties of peptoids and peptoid nanotubes, we believe that the developed multimodal DOX-loaded PepIR nanotubes in this work offer great promises for future glioma therapy in clinic.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Opinion: A critical evaluation of the evidence for aerosol invigoration of deep convection

Deep convective updraft invigoration via indirect effects of increased aerosol number concentration on cloud microphysics is frequently cited as a driver of correlations between aerosol and deep convection properties. Here, we critically evaluate the theoretical, modeling, and observational evidence for warm- and cold-phase invigoration pathways. Though warm-phase invigoration is plausible and theoretically supported via lowering of the supersaturation with increased cloud droplet concentration in polluted conditions, the significance of this effect depends on substantial supersaturation changes in real-world convective clouds that have not been observed. Much of the theoretical support for cold-phase invigoration depends on unrealistic assumptions of instantaneous freezing and unloading of condensate in growing, isolated updrafts. When applying more realistic assumptions, impacts on buoyancy from enhanced latent heating via fusion in polluted conditions are largely canceled by greater condensate loading. Many foundational observational studies supporting invigoration have several fundamental methodological flaws that render their findings incorrect or highly questionable. Thus, much of the evidence for invigoration has come from numerical modeling, but different models and setups have produced a vast range of results. Furthermore, modeled aerosol impacts on deep convection are rarely tested for robustness, and microphysical biases relative to observations persist, rendering many results unreliable for application to the real world. Without clear theoretical, modeling, or observational support, and given that enervation rather than invigoration may occur for some deep convective regimes and environments, it is entirely possible that the overall impact of cold-phase invigoration is negligible. Substantial mesoscale variability of dominant thermodynamic controls on convective updraft strength coupled with substantial updraft and aerosol variability in any given event are poorly quantified by observations and present further challenges to isolating aerosol effects. Observational isolation and quantification of convective invigoration by aerosols is also complicated by limitations of available cloud condensation nuclei and updraft speed proxies, aerosol correlations with meteorological conditions, and cloud impacts on aerosols. Furthermore, many cloud processes, such as entrainment and condensate fallout, modulate updraft strength and aerosol–cloud interactions, varying with cloud life cycle and organization, but these processes remain poorly characterized. Considering these challenges, recommendations for future observational and modeling research related to aerosol invigoration of deep convection are provided.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Novel PCM-based fin and tube heat exchanger system for building heating and cooling applications

In the United States, the building sector accounts for 40% of all energy use, and buildings are responsible for more than two-thirds of electricity consumption. Buildings remain the major driver of energy-related carbon emissions, and such emissions are projected to increase in the years ahead because of urbanization and population growth. To accomplish the low carbon energy goal in the building sector, phase change material (PCM)–based thermal energy storage (TES) is increasingly being adopted because it offers several advantages, such as reducing building peak load and energy consumption, enabling large scale deployment of renewables, and improving grid stability. The integration of TES with thermally anisotropic building envelopes (TABEs) is a promising solution because, TABE can redirect natural thermal energy from a building using hydronic loops to TES, and the stored energy can be used later for heating and cooling applications. In this study, we experimentally investigate the thermal performance of a novel fin-tube heat exchanger TES system designed for potential integration with a TABE. An experimental rig for a 5-gal PCM fin-tube heat exchanger system with water as the heat transfer medium is described which records temperatures at the heated and cooled boundaries of the system. Experimental observations provide insight into the role a TES system can play in offsetting a building’s heating and cooling demand and also offer a means to characterize the performance of PCMs for building applications. The scale and study presented in this work will help in the design of future thermal storage systems optimized for storage capacity while also accounting for overall system costs for building applications.

Tamraparni, Achutha↗
DOE OSTI2026

Challenges and Opportunities for HVAC + Phase Change Material Thermal Energy Storage in Buildings

Phase-change material (PCM) thermal-energy storage (TES) integrated with HVAC and domestic hot water (DHW) can shift a large share of building thermal loads. By flattening and shifting loads, PCM TES reduces peak electricity use, eases stress on local and grid infrastructure, and lowers costs. It can also defer costly upgrades to service panels, distribution, and transmission. Higher energy density relative to chilled or hot water storage makes PCM TES practical for small, space limited, and retrofit projects, while packaged HVAC-integrated systems expand cost-effective load shifting to commercial buildings that previously lacked options. Despite this promise, deployment faces barriers. This paper presents challenges, opportunities, and lessons learned from lab and field integrations of PCM TES with packaged HVAC systems. Key challenges include misalignment between default heat pump controls tuned for direct-to-load operation and TES charge/discharge objectives, PCM properties that diverge from manufacturer claims and evolve with cycling, and high integration and deployment costs with off-the-shelf products. These studies underscore the need for factory built, integrated systems that arrive as prepackaged modules with proven controls, reducing design and installation effort and delivering predictable performance across projects. The paper outlines steps to enable viable and scalable PCM TES HVAC and DHW systems, including 1) validated methods that can be used to characterize PCM properties and TES system performance, 2) supervisory controls that optimize charge/discharge scheduling, and 3) factory integrated packaging that eliminates bespoke field engineering.

Dutton, Spencer↗
DOE OSTI2023

Efficiency and Demand Flexibility in Large Office Buildings: The Potential for Cost Savings and CO 2 Reductions from Lighting and Cooling Measures

This report presents the estimated impact of lighting and cooling efficiency and demand flexibility measures in large office buildings in each state in the contiguous United States. It provides modeled results for three different metrics: bill savings, regional grid operational costs savings, and carbon dioxide (CO 2 ) emissions reductions. Lighting efficiency and demand flexibility are estimated to reduce load by up to 80 MWh/yr in a single large office building. These load reductions result in customer bill savings of up to $8,800/yr per building, with the highest savings in southern and midwestern states. Grid operating cost savings are estimated at up to $3,240/yr/building, with greatest benefit in southern and northeastern states. CO 2 emissions reduction potential is highest in the Dakotas, Nebraska, across the Midwest, in West Virginia, and in Mississippi (<48,200 kg/yr/building). Comparatively, cooling measures are found to have less load reduction potential (<28.5 MWh/yr/building), with the greatest potential in southern states including Texas, which ranks top of the list across several of the metrics studied. In numerous states, shifting cooling load to off-peak hours is found to increase costs and CO 2 emissions because precooling results in increased load during high-cost or high-CO 2 emissions periods. In general, focusing on cooling efficiency and load shedding has the potential for more savings. In all cases, the specific rate structure is a significant determinant in actual bill savings, which are up to $4,000/yr/building. To realize the full potential for bill savings through an energy measure, building operators must identify how the measure will change the building load pattern and the interaction of this load change with the applicable rate tariff. To realize CO 2 emissions reductions, industry and state coordination is needed to verify which fuel source is on the margin and then to create incentives for end users to reduce load during high-CO 2 emissions hours. Regular updates to data sets and analyses are critical. Regulators and policymakers are well positioned to facilitate the necessary coordination between the electric industry and building energy managers to develop appropriate price signals and incentives.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Incentivizing Distributed Energy Resource Participation in Grid Services

The bulk power system is experiencing a dramatic shift as renewable generation growth continues to accelerate. Large-scale renewables adoption will help societies transition to a low-carbon, low-cost, and environmentally friendly electrical power system. However, the transition from a paradigm of generation following load to one where load follows generation will require large-scale interconnection and coordinated operation of Distributed Energy Resources (DERs), supported by open communication protocols. In this future grid scenario, DER aggregations will provide critical grid services that enable high penetration levels of renewable generation. This position paper presents an Energy Service Interface (ESI) that defines scope for ensuring secure, trustworthy information exchange between grid service providers and DERs. The goal of the ESI is to encourage large-scale participation of DERs in order to provide grid services through dispatch of DER aggregations. This position paper also presents an open smart energy communications protocol that allows DERs to advertise their characteristics and participate in grid services, within constraints established by the ESI. The paper presents several monetization incentives that grid service providers could use to encourage large-scale DER participation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗