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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Development and Evaluation of Velocity Predictive Optimal Energy Management Strategies in Intelligent and Connected Hybrid Electric Vehicles

In this study, a thorough and definitive evaluation of Predictive Optimal Energy Management Strategy (POEMS) applications in connected vehicles using 10 to 20 s predicted velocity is conducted for a Hybrid Electric Vehicle (HEV). The presented methodology includes synchronous datasets gathered in Fort Collins, Colorado using a test vehicle equipped with sensors to measure ego vehicle position and motion and that of surrounding objects as well as receive Infrastructure to Vehicle (I2V) information. These datasets are utilized to compare the effect of different signal categories on prediction fidelity for different prediction horizons within a POEMS framework. Multiple artificial intelligence (AI) and machine learning (ML) algorithms use the collected data to output future vehicle velocity prediction models. The effects of different combinations of signals and different models on prediction fidelity in various prediction windows are explored. All of these combinations are ultimately addressed where the rubber meets the road: fuel economy (FE) enabled from POEMS. FE optimization is performed using Model Predictive Control (MPC) with a Dynamic Programming (DP) optimizer. FE improvements from MPC control at various prediction time horizons are compared to that of full-cycle DP. All FE results are determined using high-fidelity simulations of an Autonomie 2010 Toyota Prius model. The full-cycle DP POEMS provides the theoretical upper limit on fuel economy (FE) improvement achievable with POEMS but is not currently practical for real-world implementation. Perfect prediction MPC (PP-MPC) represents the upper limit of FE improvement practically achievable with POEMS. Real-Prediction MPC (RP-MPC) can provide nearly equivalent FE improvement when used with high-fidelity predictions. Constant-Velocity MPC (CV-MPC) uses a constant speed prediction and serves as a “null” POEMS. Results showed that RP-MPC, enabled by high-fidelity ego future speed prediction, led to significant FE improvement over baseline nearly matching that of PP-MPC.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2005

TRMM Re-Entry Planning: Attitude Determination and Control During Thruster Modes

The Tropical Rainfall Measuring Mission (TRMM) spacecraft has been undergoing design for a controlled re-entry to Earth. During simulation of the re-entry plan, there was evidence of errors in the attitude determination algorithms during thruster modes. These errors affected the bum efficiency, and thus planning, during re-entry. During thruster modes, the spacecraft attitude is controlled off of integrated Gyro Error Angles that were designed to closely follow the nominal spacecraft pointing frame (Tip Frame). These angles, however, were not exactly mapped to the Tip Frame from the Body Frame. Additionally, in the initial formulation of the thruster mode attitude determination algorithms, several assumptions and approximations were made to conserve processor speed. These errors became noticeable and significant when simulating bums of much longer duration (-10 times) than had been produced in flight. A solution is proposed that uses attitude determination information from a propagated extended Kalman filter that already exists in the TRMM thruster modes. This attitude information is then used to rotate the Gyro Error Angles into the Tip Frame. An error analysis is presented that compares the two formulations. The new algorithm is tested using the TRMM High-Fidelity Simulator and verified with the TRMM Software Testing and Training Facility. Simulation results for both configurations are also presented.

DeWeese, Keith↗
DOE OSTI2020

kynema-sgf [SWR-20-85]

Kynema-SGF (formerly AMR-Wind), wherein SGF stands for structured-grid fluid dynamics, is a massively parallel, block-structured adaptive-mesh, incompressible flow solver. The codebase was initiated in 2019 from incflo. The solver is built on top of the AMReX library. AMReX library provides the mesh data structures, mesh adaptivity, as well as the linear solvers used for solving the governing equations. Kynema-SGF is actively developed and maintained by a dedicated multi-institutional team from Lawrence Berkeley National Laboratory, National Laboratory of the Rockies, and Sandia National Laboratories. The primary applications for Kynema-SGF are: performing large-eddy simulations (LES) of atmospheric boundary layer (ABL) flows, simulating wind farm turbine-wake interactions using actuator disk or actuator line models for turbines, and as a background solver when coupled with a near-body solver (e.g., Kynema-UGF) with overset methodology to perform blade-resolved simulations of multiple wind turbines within a wind farm. For offshore applications, the ability to model the air-sea interaction effects and its impact on the ABL characteristics is another focus for the code development effort. As with other codes in the Kynema ecosystem, Kynema-SGF shares the following objectives: *an open, well-documented implementation of the state-of-the-art computational models for modeling wind farm flow physics at various fidelities that are backed by a comprehensive verification and validation (V&V) process; *be capable of performing the highest-fidelity simulations of flow fields within wind farms; and *be able to leverage the high-performance leadership class computing facilities available at DOE national laboratories.

Ananthan, Shreyas↗
NASA NTRS1984

Practical aspects of modeling aircraft dynamics from flight data

The purpose of parameter estimation, a subset of system identification, is to estimate the coefficients (such as stability and control derivatives) of the aircraft differential equations of motion from sampled measured dynamic responses. In the past, the primary reason for estimating stability and control derivatives from flight tests was to make comparisons with wind tunnel estimates. As aircraft became more complex, and as flight envelopes were expanded to include flight regimes that were not well understood, new requirements for the derivative estimates evolved. For many years, the flight determined derivatives were used in simulations to aid in flight planning and in pilot training. The simulations were particularly important in research flight test programs in which an envelope expansion into new flight regimes was required. Parameter estimation techniques for estimating stability and control derivatives from flight data became more sophisticated to support the flight test programs. As knowledge of these new flight regimes increased, more complex aircraft were flown. Much of this increased complexity was in sophisticated flight control systems. The design and refinement of the control system required higher fidelity simulations than were previously required.

Iliff, K. W.↗
DOE OSTI2025

Perspectives on Systematic Cloud Microphysics Scheme Development With Machine Learning

Cloud microphysics—the collection of processes that govern the small‐scale formation, evolution, and interactions of liquid droplets and ice crystals in clouds and precipitation—remains a major source of uncertainty in weather and climate models. Although too small in scale to be explicitly resolved in any large‐eddy simulation, weather, or climate model, the representation of cloud microphysical processes has significant impact at the climate scale. Current microphysical schemes are limited by both parametric uncertainty, linked to uncertainty in physical parameter values, and structural uncertainty, arising from incomplete physical understanding of the processes at play or approximations made for computational efficiency. Recent advances in the application of machine learning (ML) to the physical sciences show significant potential for minimizing these limitations by leveraging high‐fidelity simulations and observations. Here we outline the challenges that must be addressed to apply ML toward cloud microphysics scheme development. This perspectives paper synthesizes recent progress in using data‐driven methods, including ML, to improve cloud microphysics parameterizations and highlights opportunities to address key uncertainties. We discuss the roles of aleatoric (irreducible, or statistical) and epistemic (reducible, or systematic) errors in contributing to microphysics parameterization uncertainty. ML can leverage observations to improve microphysical schemes via bottom‐up and top‐down constraints. Methods such as differentiable programming and ML‐enhanced sampling strategies and the creation of large scale benchmark data sets promise to bridge the gap between observations and models and to improve the consistency of cloud microphysical representation across temporal and spatial scales.

Lamb, Kara D. [Columbia Univ., New York, NY (Unite↗
NASA NTRSDate not supplied

Phase-Free Orbital Element Model Designed to Enable Rapid Assessment of Eclipse and Radiation Profiles for Low-Thrust Spiral Transfers Around the Earth

The Gateway Power and Propulsion Element (PPE) will be the first low-thrust solar electric ion propulsion mission to transfer from a highly elliptical Earth-bound orbit to a southern near-rectilinear halo orbit (NRHO) at the Earth-Moon L2 point. Due to the low thrust nature of the transfer orbit, it is desirable to locate viable trajectories that minimize the time spent in the Van Allen radiation belts to reduce solar array degradation and keep radiation dosages below design limits. In addition to radiation, low thrust trajectories which spiral around the Earth will pass through at least one or more seasons of Earth eclipses. The solar electric propulsion system relies on sunlight to generate the power necessary to operate the ion thrusters. Therefore, it is advantageous to find trajectories which also minimize the amount of time spent in eclipse and avoid excessive battery draw-down periods. We present an analytical method which rapidly approximates low-thrust spiral trajectories, fit to high-fidelity simulated data and parameterized to allow for changes in vehicle thrust characteristics, that is post-processed to determine eclipse profiles and time spent in the belts using a novel approach that estimates the geometry of the belts using a first-order dipole approximation of the Earth’s magnetic field. This method can be used to find satisfactory launch dates and orbit orientations that can serve as initial guesses when optimizing such missions in high-fidelity software.

low thrust trajectory design↗
NASA NTRSDate not supplied

Phase-Free Orbital Element Model Designed to Enable Rapid Assessment of Eclipse and Radiation Profiles for Low-Thrust Spiral Transfers Around the Earth

The Gateway Power and Propulsion Element (PPE) will be the first low-thrust solar electric ion propulsion mission to transfer from a highly elliptical Earth-bound orbit to a southern near-rectilinear halo orbit (NRHO) at the Earth-Moon L2 point. Due to the low thrust nature of the transfer orbit, it is desirable to locate viable trajectories that minimize the time spent in the Van Allen radiation belts to reduce solar array degradation and keep radiation dosages below design limits. In addition to radiation, low thrust trajectories which spiral around the Earth will pass through at least one or more seasons of Earth eclipses. The solar electric propulsion system relies on sunlight to generate the power necessary to operate the ion thrusters. Therefore, it is advantageous to find trajectories which also minimize the amount of time spent in eclipse and avoid excessive battery draw-down periods. We present an analytical method which rapidly approximates low-thrust spiral trajectories, fit to high-fidelity simulated data and parameterized to allow for changes in vehicle thrust characteristics, that is post-processed to determine eclipse profiles and time spent in the belts using a novel approach that estimates the geometry of the belts using a first-order dipole approximation of the Earth’s magnetic field. This method can be used to find satisfactory launch dates and orbit orientations that can serve as initial guesses when optimizing such missions in high-fidelity software.

low thrust trajectory design↗
NASA NTRS2011

Time-Accurate Computational Fluid Dynamics Simulation of a Pair of Moving Solid Rocket Boosters

Since the Columbia accident, the threat to the Shuttle launch vehicle from debris during the liftoff timeframe has been assessed by the Liftoff Debris Team at NASA/MSFC. In addition to engineering methods of analysis, CFD-generated flow fields during the liftoff timeframe have been used in conjunction with 3-DOF debris transport methods to predict the motion of liftoff debris. Early models made use of a quasi-steady flow field approximation with the vehicle positioned at a fixed location relative to the ground; however, a moving overset mesh capability has recently been developed for the Loci/CHEM CFD software which enables higher-fidelity simulation of the Shuttle transient plume startup and liftoff environment. The present work details the simulation of the launch pad and mobile launch platform (MLP) with truncated solid rocket boosters (SRBs) moving in a prescribed liftoff trajectory derived from Shuttle flight measurements. Using Loci/CHEM, time-accurate RANS and hybrid RANS/LES simulations were performed for the timeframe T0+0 to T0+3.5 seconds, which consists of SRB startup to a vehicle altitude of approximately 90 feet above the MLP. Analysis of the transient flowfield focuses on the evolution of the SRB plumes in the MLP plume holes and the flame trench, impingement on the flame deflector, and especially impingment on the MLP deck resulting in upward flow which is a transport mechanism for debris. The results show excellent qualitative agreement with the visual record from past Shuttle flights, and comparisons to pressure measurements in the flame trench and on the MLP provide confidence in these simulation capabilities.

Strutzenberg, Louise L.↗
DOE OSTI2022

Integrated simulation, machine learning, and experimental approach to characterizing fracture instability in indentation pillar-splitting of materials

Measuring fracture toughness of materials at small scales remains challenging due to limited experimental testing configurations. A recently developed indentation pillar-splitting method has shown promise of improved flexibility in fracture toughness measurements at the microscale, partly due to the occurrence of an unusual fracture instability, i.e., a transition from stable to unstable crack propagation. In spite of growing interest in this method, the underlying mechanism of this phenomenon is yet to be elucidated. Furthermore, we provide a comprehensive description of fracture instability in indentation pillar-splitting by combining in situ experiments with high-fidelity simulations based on cohesive zone and J-integral methods. In addition, a machine-learning-based solution for predicting the critical indentation load of fracture instability is established through Gaussian processes regression for broad use of this method by the community.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Impact of Limited Degree of Freedom Drag Coefficients on a Floating Offshore Wind Turbine Simulation

The worldwide effort to design and commission floating offshore wind turbines (FOWT) is motivating the need for reliable numerical models that adequately represent their physical behavior under realistic sea states. However, properly representing the hydrodynamic quadratic damping for FOWT remains uncertain, because of its dependency on the choice of drag coefficients (dimensionless or not). It is hypothesized that the limited degree of freedom (DoF) drag coefficient formulation that uses only translational drag coefficients causes mischaracterization of the rotational DoF drag, leading to underestimation of FOWT global loads, such as tower base fore-aft shear. To address these hydrodynamic modeling uncertainties, different quadratic drag models implemented in the open-source mid-fidelity simulation tool, OpenFAST, were investigated and compared with the experimental data from the Offshore Code Comparison Collaboration, Continued, with Correlation (OC5) project. The tower base fore-aft shear and up-wave mooring line tension were compared under an irregular wave loading condition to demonstrate the effects of the different damping models. Two types of hydrodynamic quadratic drag formulations were considered: (1) member-based dimensionless drag coefficients applied only at the translational DoF (namely limited-DoF drag model) and (2) quadratic drag matrix model (in dimensional form). Based on the results, the former consistently underestimated the 95th percentile peak loads and spectral responses when compared to the OC5 experimental data. In contrast, the drag matrix models reduced errors in estimates of the tower base shear peak load by 7–10% compared to the limited-DoF drag model. The underestimation in the tower base fore-aft shear was thus inferred be related to mischaracterization of the rotational pitch drag and the heave motion/drag by the limited-DoF model.

17 WIND ENERGY↗
DOE OSTI2018

An Intercomparison of GCM and RCM Dynamical Downscaling for Characterizing the Hydroclimatology of California and Nevada

Abstract Dynamical downscaling is a widely used technique to properly capture regional surface heterogeneities that shape the local hydroclimatology. However, in the context of dynamical downscaling, the impacts on simulation fidelity have not been comprehensively evaluated across many user-specified factors, including the refinements of model horizontal resolution, large-scale forcing datasets, and dynamical cores. Two global-to-regional downscaling methods are used to assess these: specifically, the variable-resolution Community Earth System Model (VR-CESM) and the Weather Research and Forecasting (WRF) Model with horizontal resolutions of 28, 14, and 7 km. The modeling strategies are assessed by comparing the VR-CESM and WRF simulations with consistent physical parameterizations and grid domains. Two groups of WRF Models are driven by either the NCEP reanalysis dataset (WRF_NCEP) or VR-CESM7 results (WRF_VRCESM) to evaluate the effects of large-scale forcing datasets. The simulated hydroclimatologies are compared with reference datasets for key properties including total precipitation, snow cover, snow water equivalent (SWE), and surface temperature. The large-scale forcing datasets are critical to the WRF simulations of total precipitation but not surface temperature, controlled by the wind field and atmospheric moisture transport at the ocean boundary. No significant benefit is found in the regional average simulated hydroclimatology by increasing horizontal resolution refinement from 28 to 7 km, probably due to the systematic biases from the diagnostic treatment of rainfall and snowfall in the microphysics scheme. The choice of dynamical core has little impact on total precipitation but significantly determines simulated surface temperature, which is affected by the snow-albedo feedback in winter and soil moisture estimations in summer.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

TPSAS-NF1676L-13792-DND

Extreme structural requirements of future aerospace vehicles motivate the development of new, ultra-durable materials and game-changing methodologies for material certification and sustainment. Computational simulations spanning many orders of magnitude in length and time scales—from the nanoscale of underlying damage processes to the larger scales of continuum cracks—are being developed to support these requirements. Results of these simulations are used to deduce key aspects of material response to loads and environments, including: - The microstructural mechanics that govern metal fatigue crack initiation and growth - The variety and complexity of the dislocation-precipitate interac- tions that underpin plastic behavior and damage evolution - The energetic principles that govern the interaction of water with crack surfaces within a structural component - The mechanics of grain boundary separation Modeling the physics behind these metal fatigue behaviors is extremely complex, and requires intensive, high-fidelity simulations. The knowledge gained through these simulations, however, is forming the keystone for advanced material design and will enable development of more capable, reliable structures for aerospace vehicles.

Jacob Hochhalter↗
NASA NTRS1994

Simulation in a dynamic prototyping environment: Petri nets or rules?

An evaluation of a prototyped user interface is best supported by a simulation of the system. A simulation allows for dynamic evaluation of the interface rather than just a static evaluation of the screen's appearance. This allows potential users to evaluate both the look (in terms of the screen layout, color, objects, etc.) and feel (in terms of operations and actions which need to be performed) of a system's interface. Because of the need to provide dynamic evaluation of an interface, there must be support for producing active simulations. The high-fidelity training simulators are delivered too late to be effectively used in prototyping the displays. Therefore, it is important to build a low fidelity simulator, so that the iterative cycle of refining the human computer interface based upon a user's interactions can proceed early in software development.

Moore, Loretta A.↗
DOE OSTI2022

The DESI N -body Simulation Project – II. Suppressing sample variance with fast simulations

ABSTRACT Dark Energy Spectroscopic Instrument (DESI) will construct a large and precise three-dimensional map of our Universe. The survey effective volume reaches $\sim 20\, h^{-3}\, \mathrm{Gpc}^{3}$. It is a great challenge to prepare high-resolution simulations with a much larger volume for validating the DESI analysis pipelines. AbacusSummit is a suite of high-resolution dark-matter-only simulations designed for this purpose, with $200\, h^{-3}\, \mathrm{Gpc}^{3}$ (10 times DESI volume) for the base cosmology. However, further efforts need to be done to provide a more precise analysis of the data and to cover also other cosmologies. Recently, the CARPool method was proposed to use paired accurate and approximate simulations to achieve high statistical precision with a limited number of high-resolution simulations. Relying on this technique, we propose to use fast quasi-N-body solvers combined with accurate simulations to produce accurate summary statistics. This enables us to obtain 100 times smaller variance than the expected DESI statistical variance at the scales we are interested in, e.g. $k \lt 0.3\, h\, \mathrm{Mpc}^{-1}$ for the halo power spectrum. In addition, it can significantly suppress the sample variance of the halo bispectrum. We further generalize the method for other cosmologies with only one realization in AbacusSummit suite to extend the effective volume ∼20 times. In summary, our proposed strategy of combining high-fidelity simulations with fast approximate gravity solvers and a series of variance suppression techniques sets the path for a robust cosmological analysis of galaxy survey data.

cosmology: theory↗
DOE OSTI2017

Passive Suppression Mechanisms in Laminar Vortex-Induced Vibration of a Sprung Cylinder With a Strongly Nonlinear, Dissipative Oscillator

We study cross-flow vortex-induced vibration (VIV) of a linearly sprung circular cylinder equipped with a dissipative oscillator with cubic stiffness nonlinearity, restrained to move in the direction of travel of the cylinder. The dissipative, essentially nonlinear coupling between the cylinder and the oscillator allows for targeted energy transfer (TET) from the former to the latter, whereby the oscillator acts as a nonlinear energy sink (NES) capable of passively suppressing cylinder oscillations. For fixed values of the Reynolds number (Re = 48, slightly above the fixed-cylinder Hopf bifurcation), cylinder-to-fluid density ratio, and dimensionless cylinder spring constant, spectral-element simulations of the Navier–Stokes equations coupled to the rigid-body motion show that different combinations of NES parameters lead to different long-time attractors of the dynamics. We identify four such attractors which do not coexist at any given point in the parameter space, three of which lead to at least partial VIV suppression. We construct a reduced-order model (ROM) of the fluid–structure interaction (FSI) based on a wake oscillator to analytically study those four mechanisms seen in the high-fidelity simulations and determine their respective regions of existence in the parameter space. Asymptotic analysis of the ROM relies on complexification-averaging (CX-A) and slow–fast partition of the transient dynamics and predicts the existence of complete and partial VIV-suppression mechanisms, relaxation cycles, and Hopf and Shilnikov bifurcations. These outcomes are confirmed by numerical integration of the ROM and comparisons with spectral-element simulations of the full system.

Blanchard, Antoine↗
NASA NTRS1994

Simulation in a dynamic prototyping environment: Petri nets or rules?

An evaluation of a prototyped user interface is best supported by a simulation of the system. A simulation allows for dynamic evaluation of the interface rather than just a static evaluation of the screen's appearance. This allows potential users to evaluate both the look (in terms of the screen layout, color, objects, etc.) and feel (in terms of operations and actions which need to be performed) of a system's interface. Because of the need to provide dynamic evaluation of an interface, there must be support for producing active simulations. The high-fidelity training simulators are normally delivered too late to be effectively used in prototyping the displays. Therefore, it is important to build a low fidelity simulator, so that the iterative cycle of refining the human computer interface based upon a user's interactions can proceed early in software development.

Moore, Loretta A.↗
DOE OSTI2024

Improving the modeling of near-wall interphase heat transfer in porous media models of Pebble Bed Reactors

Here, this work aims to improve capabilities for modeling localized effects in porous media models of Pebble Bed Reactors. The wall-channeling effect is the primary local phenomenon of interest in a PBR, where the presence of the reflector wall disrupts the pebble packing, causing the pebbles near the wall to pack less efficiently and creating large void regions. Accurate modeling of the near-wall region is important as it will affect core bypass flow and temperature predictions. Porous media models are commonly used for design scoping and plant-level simulations of PBRs. Although these models have some capabilities to model the near-wall region, the correlations that are available in porous media codes are often inaccurate when a multi-region model is used to discretize the near-wall region. This work employs a high-to-low analysis to study the accuracy of available interphase heat transfer closures. NekRS, a spectral element computational fluid dynamics code, is used to perform Large Eddy Simulations. These LES simulation results are compared to porous media model results from the Pronghorn porous media code. The friction term of the KTA drag closure is first improved, reducing the error in the prediction of the near-wall velocity from over 50% to less than 5%. This is combined with improvements to the form term from previous works to produce a drag closure that is capable of accurately modeling the wall-channeling effect across a variety of flow conditions. The Nusselt number predictions of several heat transfer correlations are compared to the high-fidelity results where it is found that the KTA heat transfer correlation is capable of accurately predicting the local Nusselt numbers that were determined in the high-fidelity simulation. Comparison of the radial solid temperature profiles, however, reveal discrepancies between NekRS and Pronghorn. It is discovered that the implementation of the interphase heat transfer coefficient that exists in many current porous media codes is not valid when local porosities are modeled. Instead, it is suggested that the interphase heat transfer coefficient should be dependent on the local porosity, the Nusselt number, and the local solid surface-to-volume ratio. Implementation of this change produces improvement in the agreement between the results obtained by NekRS and Pronghorn while using the KTA heat transfer correlation.

interphase heat transfer↗
DOE OSTI2023

On the Morphodynamics of a Wide Class of Large‐Scale Meandering Rivers: Insights Gained by Coupling LES With Sediment‐Dynamics

Abstract In meandering rivers, interactions between flow, sediment transport, and bed topography affect diverse processes, including bedform development and channel migration. Predicting how these interactions affect the spatial patterns and magnitudes of bed deformation in meandering rivers is essential for various river engineering and geoscience problems. Computational fluid dynamics simulations can predict river morphodynamics at fine temporal and spatial scales but have traditionally been challenged by the large scale of natural rivers. We conducted coupled large‐eddy simulation and bed morphodynamics simulations to create a unique database of hydro‐morphodynamic data sets for 42 meandering rivers with a variety of planform shapes and large‐scale geometrical features that mimic natural meanders. For each simulated river, the database includes (a) bed morphology, (b) three‐dimensional mean velocity field, and (c) bed shear stress distribution under bankfull flow conditions. The calculated morphodynamics results at dynamic equilibrium revealed the formation of scour and deposition patterns near the outer and inner banks, respectively, while the location of point bars and scour regions around the apexes of the meander bends is found to vary as a function of the radius of curvature of the bends to the width ratio. A new mechanism is proposed that explains this seemingly paradoxical finding. The high‐fidelity simulation results generated in this work provide researchers and scientists with a rich numerical database for morphodynamics and bed shear stress distributions in large‐scale meandering rivers to enable systematic investigation of the underlying phenomena and support a range of river engineering applications.

54 ENVIRONMENTAL SCIENCES↗