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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

On the effective theory of neutrino-electron and neutrino-quark interactions

We determine the four Fermi effective theory of neutrino interactions within the Standard Model including one-loop electroweak radiative corrections, in combination with the measured muon lifetime and precision electroweak data. Including two-loop matching and three-loop running corrections, we determine lepton coefficients accounting for all large logarithms through relative order $\cal{O}(\alpha \alpha_s)$ and quark coefficients accounting for all large logarithms through ${\cal{O}}(\alpha)$. We present four-fermion coefficients valid in $n_f=3$ and $n_f=4$ flavor quark theories, as well as in the extreme low-energy limit. We relate the coefficients in this limit to neutrino charge radii governing matter effects via forward neutrino scattering on charged particles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Coupled neutronics, thermochemistry, corrosion modeling and sensitivity analyses for isotopic evolution in molten salt reactors

This study presents a computational methodology for analyzing isotopic evolution and associated uncertainties in molten salt reactors (MSRs), focusing on both fluoride- and chloride-based fuel salts. The primary goal is to enhance the understanding of isotopic behavior in MSRs and provide data to support future experimental efforts. The methodology integrates transport-coupled depletion calculations using OpenMC, equilibrium thermodynamics modeling with Thermochimica, and a corrosion model. Sensitivity analyses are performed to evaluate the impact of power density, air ingress, and humidity content on isotopic evolution in MSR concepts. This study examines representative F- and Cl-based MSR designs, highlighting the dominant influence of power density on isotopic composition, which significantly affects isotope production and depletion rates, accounting for approximately 76% of the observed variance in element concentration. Air ingress and humidity content also affect the redox potential, solubility of heavier elements, and corrosion rates, thereby altering the expected isotopic evolution in the reactor. On average, air ingress accounts for around 17% of the variance in element concentrations, while humidity explains the remaining 7%. These variances differ significantly from element to element, depending on the element’s role in depletion, redox potential evolution, and galvanic corrosion. The findings indicate that power density, air ingress, and humidity content are all critical factors for optimizing reactor design and operational strategies. Furthermore, the study provides expected ranges for key impurities in the fuel salt, which are crucial for guiding future experimental studies and refining MSR designs. Finally, this study demonstrates the importance of modeling depletion coupled with the evolution of redox potential and chemical interactions in MSR fuel salts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Influence of NOx chemistry on the prediction of natural gas end-gas autoignition in CFD engine simulations

Natural gas (NG) represents a promising low-cost/low-emission alternative to diesel fuel when used in high-efficiency internal combustion engines. Advanced combustion strategies utilizing high EGR rates and controlled end-gas autoignition can be implemented with NG to achieve diesel-like efficiencies; however, to support the design of these next-generation NG ICEs, computational tools, including single- and multi-dimensional simulation packages will need to account for the complex chemistry that can occur between the reactive species found in EGR (including NOx) and the fuel. Research has shown that NOx plays an important role in the promotion/inhibition of large hydrocarbon autoignition and when accounted for in CFD engine simulations, can significantly improve the prediction of end-gas autoignition for these fuels. However, reduced NOx-enabled NG mechanisms for use in CFD engine simulations are lacking, and as a result, the influence of NOx chemistry on NG engine operation remains unknown. Here, we analyze the effects of NOx chemistry on the prediction of NG/oxidizer/EGR autoignition and generate a reduced mechanism of a suitable size to be used in engine simulations. Results indicate that NG ignition is sensitive to NOx chemistry, where it was observed that the addition of EGR, which included NOx, promoted NG autoignition. The modified mechanism captured well all trends and closely matched experimentally measured ignition delay times for a wide range of EGR rates and NG compositions. Here, the importance of C2-C3 chemistry is noted, especially for wet NG compositions containing high fractions of ethane and propane. Finally, when utilized in CFD simulations of a Cooperative Fuels Research (CFR) engine, the new reduced mechanism was able to predict the knock onset crank angle (KOCA) to within one crank angle degree of experimental data, a significant improvement compared to previous simulations without NOx chemistry.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Thermal diffusion, exhaust gas recirculation and blending effects on lean premixed hydrogen flames

Thermodiffusively-unstable lean premixed hydrogen flames are investigated using two-dimensional direct numerical simulation employing finite-rate chemical kinetics. Three databases are generated focussing on the inclusion of the Soret effect, the recirculation of exhaust gas, and blending with methane. A simple rescaling of a classic thermal diffusion model is presented and shown to mimic multicomponent diffusion with very low computational cost and little-to-no loss in accuracy. It is also shown that a previously developed model for mean local flame speeds in lean premixed hydrogen flames can still be used provided Soret effects are taken into account in one-dimensional calculations. The addition of exhaust gas to the unburned mixture is found to enhance thermodiffusive instability; the primary mechanism for this was shown to be the highly-efficient third-body nature of water, with the reduction of adiabatic flame temperature a second-order effect. Again, the existing mean local flame speed model proved sufficient. Finally, blending with methane was found to reduce the thermodiffusive response of the flame, more so than the existing model suggests, despite adjustment of the fuel Lewis number; an adapted model is presented to account for this.

08 HYDROGEN↗
DOE OSTI2023

Validation of the single-event method for low-energy electron transport via stopping power calculations with $\mathrm{MCNP}$

Monte Carlo simulations of low-energy ( <50 keV) electron transport in matter are essential for a broad range of application fields. Several Monte Carlo codes have developed specialized treatments for this case, but a comprehensive validation of low-energy electron transport for general-purpose simulations remains lacking in the literature. One approach to accomplish this validation is calculation of stopping power using low-energy electron transport physics, as stopping power is a fundamental radiation transport quantity which must be simulated accurately for nearly any application. Here in this work, we use the Monte Carlo N-Particle (MCNP) radiation transport code with the single-event method for electron transport to calculate stopping powers of low-energy electrons (50 eV to 30 keV) in 41 elemental solids, 14 compound solids, and five rare gas solids, comparing simulation results to published semi-empirical stopping power calculations from optical measurements. In general, the simulations give good agreement (typically within ±10%) with semi-empirical stopping power values at higher energies: 300 eV and above for most elemental solids, 1 keV and above for compound solids, and 400 eV and above for rare gas solids. Agreement between MCNP and semi-empirical values is worse below these energies. The most significant source of error is the EPRDATA14 cross section data, which does not account for changes in electronic structure due to solid-state bonding, particularly in compound materials. The simplistic model of atomic excitation used to generate the EPRDATA14 cross sections is another key source of error. Additionally, the breakdown of the continuous slowing-down approximation introduces significant uncertainty at low energies, although this is a limitation of the calculation method and not of the simulation procedure. Accounting for these and other uncertainty sources, the single event method in MCNP is robust and able to give good accuracy for a variety of low-energy electron transport problems through diverse kinds of materials.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Advancing environmental assessment of the circular economy: Challenges and opportunities

The lifecycle assessment (LCA) framework is widely applied to comprehensively evaluate and improve the environmental performance of a circular economy (CE). The advances and application of LCA has been primarily restricted to evaluate the environmental performance of the CE at a micro-level, wherein the CE is implemented for a single product system. However, the CE can be operationalized at two broader levels: the meso–level (for eco-industrial parks) and the macro-level (for a city, state, or nation). Six methodological challenges emerge when applying LCA to a meso- or macro-level CE and remain unaddressed in the existing literature. This includes: selecting a relevant system boundary and functional unit, addressing data paucity and uncertainty, accounting for stakeholder behavior, assessing the trade-offs from renewable energy (RE) use, accounting for manufacturing and technology evolution, and quantifying displacement and rebound. This article proposes potential solutions and research priorities to address the above challenges.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Impact of Measured Spectrum Variation on Solar Photovoltaic Efficiencies Worldwide

In photovoltaic power ratings, a single solar spectrum, AM1.5, is the de facto standard for record laboratory efficiencies, commercial module specifications, and performance ratios of solar power plants. More detailed energy analysis that accounts for local spectral irradiance, along with temperature and broadband irradiance, reduces forecast errors to expand the grid utility of solar energy. Here, ground-level measurements of spectral irradiance collected worldwide have been pooled to provide a sampling of geographic, seasonal, and diurnal variation. Applied to nine solar cell types, the resulting divergence in solar cell efficiencies illustrates that a single spectrum is insufficient for comparisons of cells with different spectral responses. Cells with two or more junctions tend to have efficiencies below that under the standard spectrum. Silicon exhibits the least spectral sensitivity: relative weekly site variation ranges from 1% in Lima, Peru to 14% in Edmonton, Canada.

energy yield↗
DOE OSTI2025

Getting brighter: Impacts of improved day-ahead solar forecasts in high-solar, high-storage electricity systems

This paper analyzes the impacts of improved day-ahead solar forecasts on costs and dispatch in the solar-rich Southeast U.S. It uses an optimized high-solar, high-storage resource portfolio in which solar generation capacity accounts for 45 % of total installed capacity (34 %–36 % of generation) and energy storage capacity (43 GW) is equivalent to 33 % of peak demand. In a base scenario, improved day-ahead solar forecasts reduce production costs by $\$87$ million per year ($\$0.13$ per MWh load, $2023$$). This level of savings is within the range or lower than earlier studies of solar forecast improvements at lower levels of solar generation (<25 % of total generation). In this study, solar expansion was accompanied by two important sources of flexibility for managing solar forecast error: energy storage and day-ahead solar curtailment. Furthermore, the analysis finds that regional coordination complements day-ahead solar forecast improvements while natural gas commitment flexibility is a substitute for forecast improvements, as the improved solar forecast leads to sub-optimal commitment of thermal units. Day-ahead solar forecast improvements reduce reserves required to manage forecast error by 30 %. Fewer reserves to manage large, infrequent solar forecast errors could be an important benefit of improved solar forecasts.

14 SOLAR ENERGY↗
DOE OSTI2024

The influence of cloud cover on the reliability of satellite-based solar resource data

Satellite-based solar resource data are often developed and validated by using binary cloudiness categories: clear sky or overcast cloudy sky. To investigate the reliability of solar resource data in partially cloudy conditions, we estimate cloud fraction using two distinct algorithms: a physical retrieval model using surface observed global horizontal irradiance (GHI) and direct normal irradiance (DNI) and a temporal average of cloud mask data estimated by the observed DNI. Our analysis reveals a significant presence of scattered clouds, broken clouds, and mismatches between satellite- and surface-based cloud data at 17 surface sites across the contiguous United States, though confidently clear and cloudy conditions collectively account for more than 70 % of the data. Solar radiation is computed using the National Solar Radiation Database (NSRDB) algorithm and validated using surface observations. Here, our findings suggest that, in the presence of scattered clouds, NSRDB data for clear-sky conditions can be subject to significant overestimation. In cloudy-sky conditions classified by satellite data, DNI computed by the Fast All-sky Radiation Model for Solar applications with DNI (FARMS-DNI) can be underestimated when limited clouds are detected by surface observations. The bias observed in several cloudiness categories indicates that the NSRDB is exceptionally accurate in confidently clear conditions. However, clear-sky conditions with scattered clouds and mismatched cloud data contribute significantly to the overall uncertainties in the NSRDB. Therefore, future improvements in solar resource data should involve development and implementation of satellite-derived cloud fraction and should consider a novel radiative transfer model accounting for amplified cloud reflection. The evaluation within cloudiness categories also provides a physical rationale for the superior performance of FARMS-DNI compared to the Direct Insolation Simulation Code (DISC) in both cloudy-sky and all-sky conditions.

14 SOLAR ENERGY↗
DOE OSTI2025

A techno-economic assessment of carbon dioxide removal pathways via biochemical conversion of lignocellulose to biofuels and bioplastics

Biomass carbon removal and storage (BiCRS) is a promising pathway to mitigate climate change via large scale removal of atmospheric carbon dioxide (CO 2 ). We modeled several fermentation technologies, producing a variety of bioproducts from lignocellulosic feedstocks, to understand their levelized cost of CO 2 removal under multiple scenarios. Lifecycle greenhouse gas (GHG) emissions are accounted to provide cradle-to-grave estimates of carbon intensity (CI). We did not account for the avoided fossil CO 2 emissions from the use of biofuels in our CO 2 removal cost calculations, because avoided emissions do not contribute to CO 2 removal. The main products from the fermentation technologies we modeled include renewable diesel, ethanol, sustainable aviation fuel (SAF), and polyethylene (PE), with co-products including CO 2 , adipic acid, steam, and electricity. PE, depending on its end-of-life management, can serve as a form of biogenic carbon storage. PE has the potential to remove 1.2–1.5 tCO 2 per dry t-biomass, whereas biofuels have the potential to remove 0.3–0.9 tCO 2 per dry t-biomass, indicating that PE production is a more efficient method of carbon removal. We quantify costs of CO 2 removal to be $\$$60 – $\$$675 per metric tCO 2 removed across the various fermentation pathways. Under the scenarios analyzed, bioplastic production from lignocellulosic biomass is a more cost-effective route to CO 2 removal than biofuel production, with costs of CO 2 removal via bioplastics being 50–90 % lower than that of biofuels. Future research should explore the potential benefits and drawbacks of expanding bioplastic production for large-scale CO 2 removal.

09 BIOMASS FUELS↗
DOE OSTI2022

Impact of large-scale effects on mass transfer and concentration polarization in Reverse Osmosis membrane systems

Here, we present well-resolved computational fluid dynamics simulations of a large-scale reverse osmosis membrane-spacer configuration (1 m). Our computational model solves the flow and transport equations with variable solute-dependent properties. We utilize a high resolution computational mesh to resolve all relevant length scales associated with spacer-induced mixing and thin concentration boundary layers. An important contribution of this work is the development of a modified mass-transfer correlation that accounts for the development of the concentration boundary layer along the channel. A set of 2D axisymmetric simulations were performed for a spiral wound module layer with varying cross-flow conditions and spacer diameters which indicate a significant entrance length effect for concentration profile development at lower flow rates while mixing effects dominate at higher flow rates. The mass-transfer correlations at higher flow rates compare well with published correlations while a surrogate model for Sherwood number was obtained that depends on an additional similarity variable that accounted for entrance length effects at lower flow rates. Finally, a large-scale membrane-spacer design relevant to high-pressure reverse osmosis is studied with a non-uniform arrangement of spacers, which indicate a substantial saving in pressure drop (~40%) compared to traditional uniformly spaced pattern with minor variations (~2%) in concentration polarization, product water quality (~1%) and water recovery (~7%) compared to a uniform spacer pattern.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Time-lapse approach to correct deficiencies of 2D soil zymography

Membrane zymography is commonly used in rhizosphere ecology to map enzyme activities in intact soil samples and plant roots. The method consists of incubating a membrane saturated with an enzyme-specific fluorogenic substrate on the soil/root surface followed by measurements of fluorescence intensity of the product in the membrane. The traditional zymography is based on assumptions that fluorescence on membrane images is linearly increasing with time during zymography and an increase in product content is numerically equal to enzyme activity in soil below the membrane. These assumptions are unlikely to hold in experimental settings. In this work we introduce a new zymography technique, time-lapse zymography (TLZ); the approach that eliminates the need for assumptions of the traditional zymography and provides more realistic estimates of enzymatic activities. We assessed the new technique in a series of laboratory and modeling experiments, including quantification of the fluorescent product diffusion (e.g. MUF: 4-methylumbelliferone) from plant roots, enzyme activity measurements on the roots, and HYDRUS-2D & HP2 software calibration with obtained data. The calibrated model was used to analyze the processes governing spatial and temporal dynamics of MUF contents in the membrane. The results indicated that the enzyme diffusion within the membrane-soil system was negligible, and measured zymograms were adequately reproduced solely by accounting for substrate and product diffusions and for catalytic enzyme reaction described by the Michaelis-Menten equation. TLZ enabled identifying and using linear parts on MUF time series and accounting for MUF losses in each zymogram pixel, considerably improving the accuracy as compared to the traditional method. Results demonstrated that enzymatic activity from only a thin soil layer (~0.2 mm) is adequately represented in zymograms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A flexible class of priors for orthonormal matrices with basis function-specific structure

Statistical modeling of high-dimensional matrix-valued data motivates the use of a low-rank representation that simultaneously summarizes key characteristics of the data and enables dimension reduction. Low-rank representations commonly factor the original data into the product of orthonormal basis functions and weights, where each basis function represents an independent feature of the data. However, the basis functions in these factorizations are typically computed using algorithmic methods that cannot quantify uncertainty or account for basis function correlation structure a priori. While there exist Bayesian methods that allow for a common correlation structure across basis functions, empirical examples motivate the need for basis function-specific dependence structure. We propose a prior distribution for orthonormal matrices that can explicitly model basis function-specific structure. The prior is used within a general probabilistic model for singular value decomposition to conduct posterior inference on the basis functions while accounting for measurement error and fixed effects. We discuss how the prior specification can be used for various scenarios and demonstrate favorable model properties through synthetic data examples. Finally, we apply our method to two-meter air temperature data from the Pacific Northwest, enhancing our understanding of the Earth system’s internal variability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A Markov framework for generalized post-event systems recovery modeling: From single to multihazards

State-dependent models can be used to represent the system recovery process as a series of stochastic transitions from lower to higher functional states. However, the applications of these models have been limited in scope and there is a lack of a generalized recovery modeling framework. A generalized framework would permit a robust forecasting of systems and system-of-systems recovery under multiple hazards, and more broadly, would contribute to community disaster preparedness. This paper develops a generalized post hazard-event recovery modeling framework based on state-dependent Markov-type processes. We then apply the proposed framework to solve a spectrum of problems that range from hind-casting single-system recovery following a single hazard event to forecasting post-event trajectories under multiple hazards and modeling the recovery of a system-of-systems. First, Markov chains are used to hind-cast the observed recovery for a portfolio of buildings affected by the 2014 South Napa, California, earthquake. Next, Markov processes are used to formulate a parametric post hazard-event recovery model, which can be updated using Bayesian statistics when relevant datasets become available. Semi-Markov processes are then used to develop a more general model of single hazard recovery, which accounts for the intensity of the loading and level of damage caused by the event. Semi-Markov processes with non-renewal features are then used to account for multihazard interactions in a post-event recovery model, and applied to a case study that involves a community in Charleston, South Carolina. Lastly, Markov-type processes are combined with Bayesian networks to model the recovery of residential, commercial, educational, and industrial buildings (system-of-systems) following a hazard event. Overall, these applications demonstrate the versatility of the Markov framework towards handling recovery problems with varying levels of complexity.

42 ENGINEERING↗
DOE OSTI2022

Bridging confined phase behavior of CH 4 -CO 2 binary systems across scales

Phase behavior of confined fluids may deviate significantly from that of the bulk fluid due to the fluid-wall interactions being a significant portion of all intermolecular interactions under confinement. Despite recent advancements in understanding confined phase behavior of pure fluids, confined phase behavior of mixtures remains an understudied topic. In this work, we examine the confined phase behavior of a CH 4 -CO 2 binary system by combining Monte Carlo (MC) simulations, a cubic equation of state (EoS), and the lattice Boltzmann method (LBM). First, the effects of confinement on density and phase distribution in nano-size pores are established using Gibbs Ensemble MC calculations, which produce precise results of liquid and vapor confined pressures and account for the modification of the phase change location. By comparing the phase envelopes of bulk and confined mixtures at a fixed temperature, here it is observed that the phase envelopes shrink with reductions in pore size. Based on this observation, we extend a modified Peng-Robinson EoS, which was originally developed for pure fluids under confinement, to mixtures via van-der-Waals-type mixing rules and by accounting for shifts in the critical properties of confined CH 4 -CO 2 . The resulting phase envelopes are in good agreement with the MC data. In addition, a local density model is used in combination with the confined EoS to calculate adsorption isotherms of CH 4 -CO 2 mixtures and to characterize the behavior of confined matter in nanopores. Finally, we incorporate this EoS in a multicomponent multiphase LBM that uses a pseudopotential model to represent intermolecular forces. This workflow utilizes multiscale simulation techniques to bridge the behavior of multicomponent systems across scales and to shed light on the confined phase behavior of CH 4 -CO 2 binary systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Truck platooning in the U.S. national road network: A system-level modeling approach

Truck platooning enables a group of trucks to move close together, which helps reduce truck fuel use and increase effective road capacity. In this paper, a system-level equilibrium model is developed to characterize spontaneous truck platooning with coexistence of non-platooning vehicles in a network, by explicitly accounting for the interlocking relationship among platoon formation time, truck fuel saving, and increase in effective road capacity. To equilibrate the relationships, an algorithm is proposed which involves a diagonalization approach and a bush based algorithm to solve decomposed subproblems. The condition of proportionality is imposed to obtain unique traffic flows for each class of vehicles on road links. In addition, a spatially constrained multivariate clustering technique is employed to construct origin/destination zones that are smaller than the coarse Freight Analysis Framework (FAF) zones, while maintaining reasonable computational burden for network traffic assignment. Model implementation in the U.S. shows that platooning could lead to 7.9% fuel saving among platoonable trucks in 2025 and a comparable increase in effective capacity of platoonable road links, which would account for 60% of rural interstate roads. The fuel saving and road capacity improvement translate into an annual cost reduction of $\$$868 million for the U.S. intercity trucking sector and reduced road infrastructure investment needs worth $\$$4.8 billion. Extensive sensitivity analysis further reveals that fuel saving of platoonable trucks increases with platoon size but decreases with inter-truck distance in a platoon. Fuel saving potential suggests that priority should be given to rural rather than urban roads in deploying platooning technologies. As we expected, greater market penetration of platooning technologies means higher fuel saving and greater increase in effective road capacity.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Defending Weapons Inspections from the Effects of Disinformation

The intentional spread of disinformation is not a new challenge for the scientific world. We have seen it perpetuate the idea of a flat earth, convince communities that vaccines are more dangerous than helpful, and even suggest a connection between the “5G” communication infrastructure and COVID-19. Nor is disinformation a new phenomenon in the weapons inspection arena. Weapons inspectors themselves are often forced to sift through alternative narratives of events and inconsistent reporting, and they regularly see their credibility and conclusions questioned in the face of government politics or public biases. But certain recent disinformation campaigns have become so overwhelmingly comprehensive and effective that they constitute a new kind of threat. By preventing accountability for clear violations of international law, these campaigns have created a challenge to the survival of arms control treaties themselves. If weapons inspectors cannot regain the trust of the international community in the face of this challenge, it will be increasingly difficult to ensure compliance with arms control and disarmament treaties going forward. In this essay, I will briefly discuss one of the most comprehensive disinformation efforts of the past decade: the disinformation campaign used to prevent accountability for Syria's repeated use of chemical weapons. After this discussion, I will propose one possible approach to help protect the credibility of disarmament experts and weapons inspectors in the face of pervasive disinformation. This approach will require a concerted effort to connect and support compliance experts and to understand and explain their expertise across cultural, political, national, economic, and religious divides.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

A universal velocity transformation for boundary layers with pressure gradients

The logarithmic law of the wall does not capture the mean flow when a boundary layer is subjected to a strong pressure gradient. In such a boundary layer, the mean flow is affected by the spatio-temporal history of the imposed pressure gradient; and accounting for history effects remains a challenge. This work aims to develop a universal mean flow scaling for boundary layers subjected to arbitrary adverse or/and favourable pressure gradients. Here, we derive from the Navier–Stokes equation a velocity transformation that accounts for the history effects and maps the mean flow to the canonical law of the wall. The transformation is tested against channel flows with a suddenly imposed adverse or favourable pressure gradient, boundary layer flows subjected to an adverse pressure gradient, and Couette–Poiseuille flows with a streamwise pressure gradient. It is found that the transformed velocity profiles follow closely the equilibrium law of the wall.

97 MATHEMATICS AND COMPUTING↗