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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 1,099 records · Page 61

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NASA NTRS1996

Waterjet Impeller

North American Marine Jet (NAMJ), Inc. received assistance from Marshall Space Flight Center engineers in the Computational Fluid Dynamics (CFD) branch of the Structure and Dynamics Laboratory in improving the proposed design of a new impeller for their jet-propulsion systems. Marshall used advanced CFD techniques, which included creating a three-dimensional computer model of the impeller for analysis. With Marshall input, the company modified the design, then Marshall used a computer model to make a solid polycarbonate model. The rapid prototyping allowed the company to avoid many time- consuming and costly steps in creating the impeller model. NAMJ is now able to compete with Pacific-area and European manufacturers who have traditionally dominated the market.

Source record↗

NASA NTRS2004

Investigation of Acoustical Shielding by a Wedge-Shaped Airframe

Experiments on a scale model of an advanced unconventional subsonic transport concept, the Blended Wing Body (BWB), have demonstrated significant shielding of inlet-radiated noise. A computational model of the shielding mechanism has been developed using a combination of boundary integral equation method (BIEM) and equivalent source method (ESM). The computation models the incident sound from a point source in a nacelle and determines the scattered sound field. In this way the sound fields with and without the airfoil can be estimated for comparison to experiment. An experimental test bed using a simplified wedge-shape airfoil and a broadband point noise source in a simulated nacelle has been developed for the purposes of verifying the analytical model and also to study the effect of engine nacelle placement on shielding. The experimental study is conducted in the Anechoic Noise Research Facility at NASA Langley Research Center. The analytic and experimental results are compared at 6300 and 8000 Hz. These frequencies correspond to approximately 150 Hz on the full scale aircraft. Comparison between the experimental and analytic results is quite good, not only for the noise scattering by the airframe, but also for the total sound pressure in the far field. Many of the details of the sound field that the analytic model predicts are seen or indicated in the experiment, within the spatial resolution limitations of the experiment. Changing nacelle location produces comparable changes in noise shielding contours evaluated analytically and experimentally. Future work in the project will be enhancement of the analytic model to extend the analysis to higher frequencies corresponding to the blade passage frequency of the high bypass ratio ducted fan engines that are expected to power the BWB.

Gerhold, Carl H.↗

NASA NTRS2006

Investigation of Acoustical Shielding by a Wedge-Shaped Airframe

Gerhold, Carl H.↗

DOE OSTI2025

Comparison of a Full-Scale and a 1:10 Scale Low-Speed Two-Stroke Marine Engine Using Computational Fluid Dynamics

International marine shipping is a growing component of international trade; a vast majority of all the world’s goods are being transported on large ocean-going vessels. The International Maritime Organization (IMO) introduced the Energy Efficiency Design Index in 2013, a regulatory framework of associated metrics for reducing emissions of CO 2 per tonne-mile from shipping by approximately 10% each decade. Therefore, decarbonizing the maritime sector requires the development of new fuel sources. Because of the extremely large physical size of the internal combustion engines present in shipping vessels, experimental iterative development of the engine and fuel system is cost-prohibitive. Thus, the ability to perform combustion system development in a scaled platform that can be more easily operated and modeled computationally is of interest. To that end, scaling relationships are needed to translate the results from a smaller engine to a larger counterpart. Scaling studies to date have been restricted to low scaling ratios, four-stroke light-duty engines, and under-resolved computational fluid dynamic simulations that likely do not accurately capture the physics of scaling. In this work, computational models of a 1:10 scale and a full-scale two-stroke crosshead low-speed marine engine were created and validated against experiments obtained in a real 1:10 scale engine installed at Oak Ridge National Laboratory. Further, due to the large size of the full-scale engine, the model required large high-performance computing resources to be evaluated. The availability of high-performance computing resources at the Department of Energy’s Leadership Computing Facilities is an enabler of the current work. The results of the small- and large-scale engine simulations were compared to analyze the effectiveness of the appropriate scaling laws under these extreme scaling ratio conditions.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2002

Measuring the Resilience of Advanced Life Support Systems

Despite the central importance of crew safety in designing and operating a life support system, the metric commonly used to evaluate alternative Advanced Life Support (ALS) technologies does not currently provide explicit techniques for measuring safety. The resilience of a system, or the system s ability to meet performance requirements and recover from component-level faults, is fundamentally a dynamic property. This paper motivates the use of computer models as a tool to understand and improve system resilience throughout the design process. Extensive simulation of a hybrid computational model of a water revitalization subsystem (WRS) with probabilistic, component-level faults provides data about off-nominal behavior of the system. The data can then be used to test alternative measures of resilience as predictors of the system s ability to recover from component-level faults. A novel approach to measuring system resilience using a Markov chain model of performance data is also developed. Results emphasize that resilience depends on the complex interaction of faults, controls, and system dynamics, rather than on simple fault probabilities.

Bell, Ann Maria↗

NASA NTRS1994

High performance real-time flight simulation at NASA Langley

In order to meet the stringent time-critical requirements for real-time man-in-the-loop flight simulation, computer processing operations must be deterministic and be completed in as short a time as possible. This includes simulation mathematical model computational and data input/output to the simulators. In 1986, in response to increased demands for flight simulation performance, personnel at NASA's Langley Research Center (LaRC), working with the contractor, developed extensions to a standard input/output system to provide for high bandwidth, low latency data acquisition and distribution. The Computer Automated Measurement and Control technology (IEEE standard 595) was extended to meet the performance requirements for real-time simulation. This technology extension increased the effective bandwidth by a factor of ten and increased the performance of modules necessary for simulator communications. This technology is being used by more than 80 leading technological developers in the United States, Canada, and Europe. Included among the commercial applications of this technology are nuclear process control, power grid analysis, process monitoring, real-time simulation, and radar data acquisition. Personnel at LaRC have completed the development of the use of supercomputers for simulation mathematical model computational to support real-time flight simulation. This includes the development of a real-time operating system and the development of specialized software and hardware for the CAMAC simulator network. This work, coupled with the use of an open systems software architecture, has advanced the state of the art in real time flight simulation. The data acquisition technology innovation and experience with recent developments in this technology are described.

Cleveland, Jeff I., II↗

NASA NTRS1995

DREAMS and IMAGE: A Model and Computer Implementation for Concurrent, Life-Cycle Design of Complex Systems

Computing architectures are being assembled that extend concurrent engineering practices by providing more efficient execution and collaboration on distributed, heterogeneous computing networks. Built on the successes of initial architectures, requirements for a next-generation design computing infrastructure can be developed. These requirements concentrate on those needed by a designer in decision-making processes from product conception to recycling and can be categorized in two areas: design process and design information management. A designer both designs and executes design processes throughout design time to achieve better product and process capabilities while expanding fewer resources. In order to accomplish this, information, or more appropriately design knowledge, needs to be adequately managed during product and process decomposition as well as recomposition. A foundation has been laid that captures these requirements in a design architecture called DREAMS (Developing Robust Engineering Analysis Models and Specifications). In addition, a computing infrastructure, called IMAGE (Intelligent Multidisciplinary Aircraft Generation Environment), is being developed that satisfies design requirements defined in DREAMS and incorporates enabling computational technologies.

Hale, Mark A.↗

DOE OSTI2024

Computer vision models enable mixed linear modeling to predict arbuscular mycorrhizal fungal colonization using fungal morphology

Abstract The presence of Arbuscular Mycorrhizal Fungi (AMF) in vascular land plant roots is one of the most ancient of symbioses supporting nitrogen and phosphorus exchange for photosynthetically derived carbon. Here we provide a multi-scale modeling approach to predict AMF colonization of a worldwide crop from a Recombinant Inbred Line (RIL) population derived from Sorghum bicolor and S. propinquum . The high-throughput phenotyping methods of fungal structures here rely on a Mask Region-based Convolutional Neural Network (Mask R-CNN) in computer vision for pixel-wise fungal structure segmentations and mixed linear models to explore the relations of AMF colonization, root niche, and fungal structure allocation. Models proposed capture over 95% of the variation in AMF colonization as a function of root niche and relative abundance of fungal structures in each plant. Arbuscule allocation is a significant predictor of AMF colonization among sibling plants. Arbuscules and extraradical hyphae implicated in nutrient exchange predict highest AMF colonization in the top root section. Our work demonstrates that deep learning can be used by the community for the high-throughput phenotyping of AMF in plant roots. Mixed linear modeling provides a framework for testing hypotheses about AMF colonization phenotypes as a function of root niche and fungal structure allocations.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Emerging systems biology approaches in nanotoxicology: Towards a mechanism-based understanding of nanomaterial hazard and risk

Engineered nanomaterials are being developed for a variety of technological applications. However, the increasing use of nanomaterials in society has led to concerns about their potential adverse effects on human health and the environment. During the first decade of nanotoxicological research, the realization has emerged that effective risk assessment of the multitudes of new nanomaterials would benefit from a comprehensive understanding of their toxicological mechanisms, which is difficult to achieve with traditional, low-throughput, single end-point oriented approaches. Therefore, systems biology approaches are being progressively applied within the nano(eco)toxicological sciences. This novel paradigm implies that the study of biological systems should be integrative resulting in quantitative and predictive models of nanomaterial behaviour in a biological system. To this end, global ‘omics’ approaches with which to assess changes in genes, proteins, metabolites, etc. are deployed allowing for computational modelling of the biological effects of nanomaterials. Here, we highlight omics and systems biology studies in nanotoxicology, aiming towards the implementation of a systems nanotoxicology and mechanism-based risk assessment of nanomaterials. - Highlights: • Systems nanotoxicology is a multi-disciplinary approach to quantitative modelling. • Transcriptomics, proteomics and metabolomics remain the most common methods. • Global “omics” techniques should be coupled to computational modelling approaches. • The discovery of nano-specific toxicity pathways and biomarkers is a prioritized goal. • Overall, experimental nanosafety research must endeavour reproducibility and relevance.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Using an Explainable Machine Learning Approach to Characterize Earth System Model Errors: Application of SHAP Analysis to Modeling Lightning Flash Occurrence

Abstract Computational models of the Earth System are critical tools for modern scientific inquiry. Efforts toward evaluating and improving errors in representations of physical and chemical processes in these large computational systems are commonly stymied by highly nonlinear and complex error behavior. Recent work has shown that these errors can be effectively predicted using modern Artificial Intelligence (A.I.) techniques. In this work, we go beyond these previous studies to apply an explainable A.I. technique to not only predict model errors but also move toward understanding the underlying reasons for successful error prediction. We use XGBoost classification trees and SHapley Additive exPlanations analysis to explore the errors in the prediction of lightning occurrence in the NASA Goddard Earth Observing System model, a widely used Earth System Model. This explainable error prediction system can effectively predict the model error and indicates that the errors are strongly related to convective processes and the characteristics of the land surface.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Computer vision models and advanced TEM imaging for microstructures of irradiated AM316 stainless steels

Advancements were made in automating microscopy-based material characterization, particularly in studying irradiation effects on additively manufactured (AM) materials using machine learning (ML) and computer vision (CV). These automation efforts address the challenges of analyzing complex microstructures, accelerating the detection of irradiation-induced defects. Two CV models were developed at Argonne National Laboratory (ANL) to enhance transmission electron microscopy (TEM) analysis of irradiated AM 316 stainless steel. The first model focused on the detection of irradiation-induced dislocation loops, which contribute to material hardening and embrittlement. These loops, categorized as faulted or perfect, were automatically detected and classified using a Mask R-CNN model trained on TEM images from both in-situ and ex-situ ion irradiation experiments. The model achieved high accuracy, with precision, recall, and F1 scores of 0.839, 0.734, and 0.776, respectively, demonstrating its effectiveness in analyzing dislocation loops in irradiated AM materials. The second CV model was developed to analyze the size and wall thickness of dislocation cells in laser powder bed fusion (LPBF) 316 stainless steel. Using a U-Net++ architecture with EfficientNet as the encoder, the model was trained on TEM images to segment and measure cell size and wall thickness.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Review of multi-fidelity models

Multi-fidelity models provide a framework for integrating computational models of varying complexity, allowing for accurate predictions while optimizing computational resources. These models are especially beneficial when acquiring high-accuracy data is costly or computationally intensive. This review offers a comprehensive analysis of multi-fidelity models, focusing on their applications in scientific and engineering fields, particularly in optimization and uncertainty quantification. It classifies publications on multi-fidelity modeling according to several criteria, including application area, surrogate model selection, types of fidelity, combination methods and year of publication. The study investigates techniques for combining different fidelity levels, with an emphasis on multi-fidelity surrogate models. Here this work discusses reproducibility, open-sourcing methodologies and benchmarking procedures to promote transparency. The manuscript also includes educational toy problems to enhance understanding. Additionally, this paper outlines best practices for presenting multi-fidelity-related savings in a standardized, succinct and yet thorough manner. The review concludes by examining current trends in multi-fidelity modeling, including emerging techniques, recent advancements, and promising research directions.

42 ENGINEERING↗

DOE OSTI2017

Crystallization and Thermoelectric Transport in Semiconductor Micro- and Nanostructures Under Extreme Conditions

This project focused on thermoelectric transport in semiconductor micro and nanostructures where moderate and typical operating voltages and currents lead to extreme thermal gradients and current densities. Models that describe behavior of semiconducting materials typically assume an equilibrium condition or slight deviations from it. In these cases the generation-recombination processes are assumed to have reached a local equilibrium for a given temperature. Hence, free carrier concentrations and their mobilities, band-gap, thermal conductivity, thermoelectric properties, mobility of atoms and mechanical properties of the material, can be described as a function of temperature. In the case of PN junctions under electrical bias, carrier concentrations can change up to ~ 1020 cm-3 and a drift-diffusion approximation is typically used to obtain the carrier concentrations while assuming that the material properties do not change. In non-equilibrium conditions, the assumption that the material properties remain the same may not be valid. While the increased conduction-band electron concentration may not have a drastic effect on the material, large hole concentration is expected to soften the material as ‘a hole’ comes into existence as a broken bond in the lattice. As the hole density approaches 1022 cm-3, the number of bonds holding the lattice together is significantly reduced, making it easier to break additional bonds, reduce band-gap and inhibit phonon transport. As these holes move away from where they were generated, local properties are expected to deviate significantly from the equilibrium case. Hence, temperature alone is not sufficient to describe the behavior of the material. The behavior of the solid material close to a molten region (liquid-solid interfaces) is also expected to deviate from the equilibrium case as a function of hole injection rate, which can be drastically increased or decreased in the presence of an electric field. In the past years we have investigated the possible thermoelectric explanation of asymmetric melting of self-heated Si micro-structures using equilibrium materials’ properties that exist in the literature. We have analyzed the contribution of the electrons and the holes and identified the generation-transport-recombination of minority carriers (GTR) as the reason for an extreme change in the thermal profile in presence of strong generation and electric field. A more complete analysis required construction of models that capture the individual generation and recombination processes to understand the thermal profile as well as the possibility of electronic softening and non-equilibrium melting of the structure below melting temperature. The possibility of melting a material at a lower temperature breaks the correlation between the atomic mobility and the kinetic energy in the system for a given temperature and may allow alternative growth processes. This may also be the mechanism behind ‘amorphization-without-melting in layered structures heated with laser pulses’ that has been reported earlier. The conventional models for semiconductors are constructed for low temperature operation and their projections to higher temperatures do not yield reasonable carrier concentrations. Using these models, the free hole concentrations are calculated to be on the order of 1019 cm-3 at melting, which also do not correlate well with the latent heat of fusion. The melt is expected to correspond to broken bond concentrations on the order of the atomic density (~5x1022 cm-3 for Silicon). Hence, using conventional models the thermoelectric contribution expected from the GTR process is estimated to be much smaller than it likely is. Our work focused on improving the computational models and electrical characterization of materials and devices to better understand thermoelectric trabsport under extremen thermal gradients and current densities. Specifically, during this project, we have - Expanded our computational models to include self-consistent solution of Poisson charge equation (together with current and heat equations currently solved) for improved accuracy of role of bipolar conduction, - Developed a crystallization model incorporating experimentally determined nucleation rates and growth velocities to enable simulation of grain growth, growth-from-melt, filament formation and retention, - Performed high-temperature characterization of relevant materials (including metal contacts, interfacial and insulation layers); electrical and thermal conductivities, Seebeck coefficient, carrier mobility and concentration, - Performed High-speed device-level characterization of metastable amorphous and crystalline phases, crystallization and amorphization dynamics, melting and crystalline growth-from-melt, - Observed and characterized formation of microplasmas in electrically stressed ZnO nanoforests.

36 MATERIALS SCIENCE↗

DOE OSTI2019

An Objective and Efficient Method for Assessing the Impact of Reduced-Precision Calculations On Solution Correctness

Recent studies have shown that reducing the precision of floating-point calculations in an atmospheric model can improve the models' computational performance without affecting model fidelity, but code changes are needed to accommodate lower precision, and a small number of calculations might need to retain higher precision to prevent undue round-off error. For complex and computationally expensive systems like the Energy Exascale Earth System Model (E3SM), a method is needed to objectively assess the quality of the lower-precision simulations and to quickly identify problematic code pieces This paper demonstrates that solution correctness can be evaluated through a simple and quantitative error metric based on time step convergence. The proposed test method can unambiguously detect the accumulation of precision error and objectively assess its impact on solution accuracy. Since fast physical processes are known to affect key features of the multi-year mean climate in an atmospheric model, we show that the convergence test applied to short simulations can provide useful information about the impact of reduced precision on a model’s long-term behavior. In contrast, the traditional way of climate model evaluation requires multi-year simulations and involves inspecting many physical quantities for statistical significance in the presence of natural variability. The simplicity, computational efficiency, and objectivity of the proposed method makes it very attractive for high-resolution model development. The method is also expected to be applicable to other models that numerically solve time evolution equations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Modeling the Drying of a Mock Used Fuel Assembly with COBRA-SFS Cycle-4 - 18597

The processing and storage of nuclear fuel is an ever increasingly pressing issue. Around 70,000 tons of used fuel are currently in either dry or wet storage on site at nuclear power plants or at specified spent fuel storage facilities. Additionally, about 2,000 tons are added to that sum each year. To promote retrievability, limit degradation in the canister, and reduce potential for hydrogen generation, spent fuel that is initially in wet storage must be dried before moving to dry cask storage. Therefore, this research seeks to use a mock used fuel storage cask to replicate the conditions in the industry during the drying process of fuel being moved from storage pools. To simulate this, a mock storage cask has been constructed to closely resemble those used in industry such that any areas that tend to retain water are replicated effectively. It is able to hold one mock used fuel assembly. The assembly used is an AREVA 10A 10 x 10 assembly with 78 rods filled with depleted uranium, 12 heater rods to simulate decay heat, a 3 x 3 BWR water channel, and one interchangeable rod position for tests such as a simulated failed fuel rod, BWR water rod, and PWR guide tube tests. The industry standard procedure is used in drying the assembly which involves stepping the system pressure down and holding for certain periods until reaching 3 torr and holding for 30 minutes. This is believed to sufficiently dry the assembly. The goal is to record data throughout these tests that can provide the industry with a greater understanding of how well the process works. This data will also be used to develop and validate a computer model of the drying process. Mechanistic models are currently under development. Reduced order models are being investigated for incorporation into current related engineering codes such as COBRA-SFS. COBRA-SFS is a member of the COBRA family of codes which is mainly used in the evaluation of thermal hydraulic systems containing spent nuclear fuel. However, it does not currently have the capability to account for processes such as evaporation encountered during drying operations. Therefore, those physical models are to be added to the source code. At present a model of the experiment has been created using the COBRA-SFS Cycle-4 code. A number of steady state models along with transient models have been developed and presented. Each of these yield valuable results for comparison with the experiments conducted. In addition to comparison with experimental results, the data collected from COBRA-SFS is compared with that which has been generated from other computer models which utilize computational fluid dynamics. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1995

Inductive Approaches to Improving Diagnosis and Design for Diagnosability

The first research area under this grant addresses the problem of classifying time series according to their morphological features in the time domain. A supervised learning system called CALCHAS, which induces a classification procedure for signatures from preclassified examples, was developed. For each of several signature classes, the system infers a model that captures the class's morphological features using Bayesian model induction and the minimum message length approach to assign priors. After induction, a time series (signature) is classified in one of the classes when there is enough evidence to support that decision. Time series with sufficiently novel features, belonging to classes not present in the training set, are recognized as such. A second area of research assumes two sources of information about a system: a model or domain theory that encodes aspects of the system under study and data from actual system operations over time. A model, when it exists, represents strong prior expectations about how a system will perform. Our work with a diagnostic model of the RCS (Reaction Control System) of the Space Shuttle motivated the development of SIG, a system which combines information from a model (or domain theory) and data. As it tracks RCS behavior, the model computes quantitative and qualitative values. Induction is then performed over the data represented by both the 'raw' features and the model-computed high-level features. Finally, work on clustering for operating mode discovery motivated some important extensions to the clustering strategy we had used. One modification appends an iterative optimization technique onto the clustering system; this optimization strategy appears to be novel in the clustering literature. A second modification improves the noise tolerance of the clustering system. In particular, we adapt resampling-based pruning strategies used by supervised learning systems to the task of simplifying hierarchical clusterings, thus making post-clustering analysis easier.

Fisher, Douglas H.↗

DOE OSTI2017

Bounding the Chemistry Conditions in the HM Solvent Extraction Process Criticality Safety Analyses

An approach new to the H-Canyon facility criticality safety analysis has been performed using highly detailed models of the H-Modified (HM) process mixer settlers. The HM process uses tributyl phosphate (TBP) in organic n-paraffin to extract and purify uranium from used nuclear fuel. This occurs in two cycles of counter-current solvent extraction. The aqueous stream is a weak to moderate nitric acid and the feed stock is an aqueous stream. The first Cycle, consisting of two 16-stage banks (A and B-Banks) and one 12-stage bank (C-Bank), is a three step process that separates uranium from the fuel matrix, fission products, and most of the transuranic actinide content. The first Cycle aqueous product is concentrated, adjusted for acidity and fed to the second Cycle. The second Cycle, consisting of one 16-stage bank (D-Bank) and one 12-stage bank (E-Bank), is a two-step process that further purifies the uranium and removes to a great extent remaining actinides and fission products Each stage of the mixer settler banks is modeled as three unique compositions: the mixer as a combined composition of aqueous and organic components and the settler one aqueous and one organic component. This work addresses what is believed to be normal, credible abnormal, and beyond credible abnormal conditions for a particular postulated series of process parameter upsets. The level of detail and the source for the stage-wise compositions are both new and unique to criticality safety analyses of the HM process. Initial work was presented in Ref. 1 and has since been refined. A predictive chemistry model for flowsheet development has been used to solve the solvent extraction equations for the prescribed conditions and the output of that model was then transformed into compositions for each mixture in each stage. The remaining question upon which to achieve consensus is if the approach was appropriately conservative by concluding the chemistry is appropriately bounded. Computational modeling for criticality calculations was performed using KENO-VI in the SCALE 6.1 code package. Computational modeling of the chemistry was performed using the SEPHIS Modification 4 code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Multi-qubit entanglement and algorithms on a neutral-atom quantum computer

Gate model quantum computers promise to solve currently intractable computational problems if they can be operated at scale with long coherence times and high fidelity logic. Neutral atom hyperfine qubits provide inherent scalability due to their identical characteristics, long coherence times, and ability to be trapped in dense multi-dimensional arrays. Combined with the strong entangling interactions provided by Rydberg states, all the necessary characteristics for quantum computation are available. Here we demonstrate several quantum algorithms on a programmable gate model neutral atom quantum computer in an architecture based on individual addressing of single atoms with tightly focused optical beams scanned across a two-dimensional array of qubits. Preparation of entangled Greenberger-Horne-Zeilinger (GHZ) states with up to 6 qubits, quantum phase estimation for a chemistry problem, and the Quantum Approximate Optimization Algorithm (QAOA) for the MaxCut graph problem are demonstrated. These results highlight the emergent capability of neutral atom qubit arrays for universal, programmable quantum computation, as well as preparation of non-classical states of use for quantum enhanced sensing.

97 MATHEMATICS AND COMPUTING↗