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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Modeling a Hypothetical Fusion Blanket Design Using MELCOR-TMAP

MELCOR (not an acronym) is a nuclear safety code developed by Sandia National Laboratories for the Nuclear Regulatory Commission. Idaho National Laboratory collaborates with Sandia to maintain and develop a version of MELCOR specifically for fusion device applications. Most recently, the tritium migration analysis program (TMAP) has been incorporated into MELCOR for fusion, in a version called MELCOR-TMAP. We show the results applying MELCOR-TMAP to model steady-state inventory and tritium retention in a liquid immersion blanket design for a hypothetical fusion device under steady-state operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Fuel Injection Dynamics and Composition Effects on RDE Performance

Rotating detonation engines (RDEs) provide a promising route to substantially increasing cycle efficiency in stationary gas turbines. Much of this increase relies on the ability to achieve consistent pressure gain within the combustor. In particular, the design of injectors that feed fuel and air into the detonation channel plays a crucial role. Such injectors have to ensure proper mixing of fuel and oxidizer, while minimizing backflow of detonation products into the feed plenums, and reduce susceptibility to the complex wave structures that exist within the combustor. From a practical perspective, such RDEs also need to operate with variable fuel composition. When fuel mixtures with components that possess vastly different oxidation pathways and time-scales are used, there could be additional losses through deflagrative burning instead of detonation-driven heat release. Such sensitivity to the complete flow path is akin to the physics of thermoacoustic instabilities in conventional gas turbines. In this sense, RDEs pose a unique research challenge: the performance of the device relies on the small-scale heat release process, which is highly dependent on the flow interactions within the full-scale system. As a result, canonical flow configurations, instrumented with detailed diagnostics or modeled using high-fidelity tools, but only focus on the small-scale processes will not contain the key system-level interactions. At the same time, macroscopic measurements and models that only capture system-level performance will not provide insight into the key sources of pressure losses. These couplings and sensitivities provide a formidable challenge to both experimental and simulation studies of the effects Thus, a joint experimental/computational program designed specifically to address these challenges was undertaken in this program. The focus of this program was on two key topics: a) the interaction between injector flow and the overall wave dynamics within the combustor, and b) the deflagration/detonation structure in multi-component fuels that are of practical interest. Both topics involve interaction of small-scale heat release processes with the geometry-dependent wave structure. Studies focused on the study of full-scale RDE systems, based on a 6-inch conventional annular geometry. Experimentally RDEs were studied using a combination of diagnostics. A combination of optical diagnostics and aero-thermo-acoustic analysis based on a combination of spectral and mode decomposition analysis was used to identify the dynamics of the detonation wave and other secondary waves that exist in the system. These studies have helped the identification and investigation of injector and detonation dynamics arising from coupling, and how they affect RDE mixing, detonation structure, operability and performance. Performance of RDEs was investigated through thrust stand measurements, which was used to evaluate the effective pressure gain generated by the system through the concept of equivalent available pressure. Optical diagnostics were developed and implemented to investigate the distribution of heat release, across the detonation wave. Novel optical diagnostics of NIR imaging was also developed and applied to investigate the high temperature / high pressure distribution across the detonation wave. In order to complement the experiments, the computational tools were geared to simulate the full experimental setup. GPU-based acceleration of the models and computations were developed to enable rapid simulation of the full system. In addition, the use of adaptive mesh refinement, and unstructured grid formulation, enabled the investigation of realistic geometries studied in the laboratory. The simulations produced a wealth of detail on the structure of the detonation wave under different operating conditions. Emphasis was placed on quantifying mixture pre-burning and the impact on wave propagation and structure.

03 NATURAL GAS↗
DOE OSTI2024

Disruption avoidance via island suppression: the crucial roles of DIII-D and foundational research

The FESAC long range plan calls out disruption avoidance and mitigation as key remaining technical gaps. In discussing the roles of DIII-D and NSTX-U, the FESAC long range plan says “Additional research on these facilities, in combination with private and international collaborations, continuing support of existing university tokamak programs, and utilization of US expertise in theory and simulation, is needed to find solutions to remaining technical gaps. These gaps include disruption prediction, avoidance, and mitigation …”. Disruptions pose an existential threat to ITER and to FPPs. For a fusion reactor, unplanned shutdowns caused by disruptions will be a significant barrier to connecting such a reactor to the electric grid, even if disruption mitigation is successful. Disruption studies for ITER in recent years have largely focused on disruption mitigation (e.g., pellet injection), motivated by near-term deadlines for finalizing the design of the mitigation hardware. It is recognized, however, that mitigation alone will not suffice. The 2022 U.S. ITER Research Needs Workshop Report states that ”[d]isruptions are considered the largest threat to the ITER Research Program”, and that “[m]itigation should be a last resort”. As we discuss below, there are unresolved foundational issues that play a critical role in avoidance, and DIII-D is an ideal device for generating the data needed to address these issues.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Developing and Managing Data Acquisition Software Using Spack

The Data Acquisition systems of particle physics experiments regularly push the boundaries of high-throughput computing, demanding low-latency collection of data from thousands of devices, collating data into time-sliced events, processing these events and making trigger decisions, and writing the selected data streams to disk. To accomplish these tasks, the DAQ Engineering and Operations department at Fermilab leverages multiple software libraries and builds reusable DAQ frameworks on top. These libraries must be delivered in well-defined bundles and are thoroughly tested for compatibility and functionality before being deployed to live detectors. We have several techniques used to ensure that a consistent set of dependencies can be delivered and re-created at need. We must also support active development of DAQ software components, ideally in an environment as close as possible to that of the detectors. This development often occurs across multiple packages which have to be built in concert and features tested in a consistent and reproducible manner. I will present our scheme for accomplishing these goals using Spack environments, bundle packages, and Github Actions-based CI.

Flumerfelt, Eric [Fermilab]↗
DOE OSTI2026

Center for Integrated Simulation of Fusion Relevant RF Actuators

This project was part of the “Center for Integrated Simulation of Fusion Relevant RF Actuators” SciDAC-4 project, led by Dr. Paul Bonoli (MIT). Rather than use an acronym (CISFRRFA), the project will be referred to in this document as the “RF-SciDAC4”. The larger SciDAC-4 project goals were to: 1. Develop an integrated simulation of the antenna + sheath + scrape-off-layer + core plasma system which fully utilizes leadership class computing resources to move towards a quantitative predictive capability for the response to RF power. 2. Work closely with the SciDAC-4 Whole Device Modeling (WDM) community to make both our new code development efforts, as well as the established hierarchy of RF tools, available within their environment, and to utilize WDM technologies to implement the couplings below. 3. Validate this predictive capability on appropriately diagnosed experiments including dedicated RF test stands, linear devices, and existing tokamaks. 4. Use these tools to inform design of robust, impurity-mitigating RF heating and current drive sources for future fusion devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Quantum coherent devices with reduced energy dissipation

The disclosed technology can be used to increase lifetimes of quantum coherent devices such as qubits including transmons and xmons and to reduce the losses in resonators. Energy stored in superconducting devices can be lost by emission of phonons that couple to the environment. Defects in one or more materials in the quantum coherent device can cause the coupling to phonons. Patterning one or more of the layers creates a phononic bandgap that reduces or eliminates the emission of the phonons to the environment. The energy then couples back to the quantum coherent device.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Plasmonic energy conversion device for vapor generation

The present invention is related to using a plasmonic energy conversion device comprised of a non-permeable substrate and of a plurality of nanorods, either free standing or embedded in aluminum matrix, that utilizes plasmons to generate vapor from a fluid as a result of being exposed to radiation. Methods of manufacturing the plasmonic energy converter device are described.

14 SOLAR ENERGY↗
DOE OSTI2022

Evaluation of Portable Programming Models to Accelerate LArTPC Detector Simulations

The Liquid Argon Time Projection Chamber (LArTPC) technology is widely used in high energy physics experiments, including the upcoming Deep Underground Neutrino Experiment (DUNE). Accurately simulating LArTPC detector responses is essential for analysis algorithm development and physics model interpretations. Accurate LArTPC detector response simulations are computationally demanding, and can become a bottleneck in the analysis workflow. Compute devices such as General-Purpose Graphics Processing Units (GPGPUs) have the potential to substantially accelerate simulations compared to traditional CPU-only processing. The software development that requires often carries the cost of specialized code refactorization and porting to match the target hardware architecture. With the rapid evolution and increased diversity of the computer architecture landscape, it is highly desirable to have a portable solution that also maintains reasonable performance. We report our ongoing effort in evaluating Kokkos as a basis for this portable programming model using LArTPC simulations in the context of the Wire-Cell Toolkit, a C++ library for LArTPC simulations, data analysis, reconstruction and visualization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Renewal: Coherent control of spin states in organic electronics – discovery and investigation of complex room-temperature magnetic quantum excitations

In the course of four funding cycles of this project, its research focused on the exploration and understanding of spin-dependent electronic processes in organic semiconductors. It aimed to investigate the potential of harnessing the spin degree of freedom in organic materials for various applications such as spin electronics, quantum information, sensors, and as well as quantum coherent spin phenomena of charge carrier states in organic semiconductors, with the aim to develop room-temperature-based quantum applications. Specifically, the project aimed to: Apply new diagnostic tools, i.e. spin spectroscopy techniques, for paramagnetic charge carrier states in organic semiconductors, based on coherent control with pulsed electron spin resonance to understand spin relaxation and spin mixing mechanisms in organic semiconductor materials and devices such as OLEDs. Explore the nature of charge carrier spin-coupling and pathways for its manipulation to control the physical behaviors of these materials. This involves investigating spin interactions through materials structure, composition, morphological dependencies, isotopic effects, and externally applied electric and magnetic fields, with the goal to manipulate electrical and optical material properties by adjusting spin-orbit, spin-dipolar, spin-exchange, as well as spin-hyperfine interactions to open up this materials class for new applications. Study spin-dependent charge carrier transport and recombination and how these observables are governed by spin-propagation, especially coherent spin propagation as well as collective spin-effects such as the spin-Dicke effect and resonant multi-photon magnetic dipole transitions. The project utilized pulsed electrically detected magnetic resonance (pEDMR) and pulsed optically detected magnetic resonance (pODMR) techniques over a wide frequency range. These techniques enabled the observation and quantification of various spin-spin coupling types, including spin-exchange, spin-dipolar, hyperfine, and spin-orbit interactions. The project will leverage low- to mid-frequency pEDMR/pODMR facilities and collaboration with the National High Magnetic Field Laboratory.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Excited-State and Nonadiabatic Molecular Dynamics Methods with Broad Applicability

Electronically excited states play a pivotal role in the capture, transformation, storage, and emission of radiative energy. Despite much recent progress for small model systems, excited state properties and dynamics in many larger molecular devices and materials have remained elusive for experiment and theory. Nonadiabatic transitions between electronic states turn radiative energy into heat and are particularly difficult to control. This project aims to develop new electronic structure and nonadiabatic molecular dynamics (NAMD) methods to simulate, predict, and ultimately control the flow and transformation of excitation energy in a wide-range of light-driven molecular devices such as dyes, photocatalysts, and fluorescence emitters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

MPEX AI Digital Twins

All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Spin Transport in Ferromagnet-InSb Nanowire Quantum Devices

Signatures of Majorana zero modes (MZMs), which are the building blocks for fault-tolerant topological quantum computing, have been observed in semiconductor nanowires (NW) with strong spin-orbital-interaction (SOI), such as InSb and InAs NWs with proximity-induced superconductivity. Realizing topological superconductivity and MZMs in this most widely-studied platform also requires eliminating spin degeneracy, which is realized by applying a magnetic field to induce a helical gap. Yet, the applied field can adversely impact the induced superconducting state in the NWs and also places geometric restrictions on the device, which can affect scaling of future MZM-based quantum registers. These challenges could be circumvented by integrating magnetic elements with the NWs. With this motivation, in this work we report the first experimental investigation of spin transport across InSb NWs, which are enabled by devices with ferromagnetic (FM) contacts. We determine signatures of spin polarization and spin-dependent transport in the quasi-one-dimensional ballistic regime. Moreover, we show that electrostatic gating tunes the observed magnetic signal and also reveals a transport regime where the device acts as a spin filter. These results open an avenue towards developing MZM devices in which spin degeneracy is lifted locally, without the need of an applied magnetic field. They further provide a path for realizing spin-based devices that leverage spin-orbital states in quantum wires.

1D ballistic spin transport↗
DOE OSTI2024

Tuning Fabrication Factors for Reduced Graphene Oxide Forward Osmosis Membranes

Forward osmosis (FO) may serve as a near-zero energy approach for wastewater management and selective chemical enrichment with an appropriate FO membrane. There is a need for novel FO membranes with better physical stability, chemical compatibility, and enhanced reverse flux selectivity. In this work, we have systematically studied a variety of factors for fabricating thermally reduced graphene oxide (RGO) FO filtration membranes and have demonstrated that with a comparable water flux, the RGO membranes have an exceptionally large reverse flux selectivity with 1.5 M sodium sulfate draw solution, about 7 times larger than that of cellulose triacetate membranes under the same testing condition. The interlayer spacing of the membranes can be fine-tuned by varying temperatures, so that the free interlayer spacing is less than 0.7 nm after exposure to water. The RGO-based membranes offer a few advantages with high reverse flux selectivity, mechanical robustness with strong adhesion to nylong support membranes without damage after FO tests and tape peel tests, and enhanced chromate and chlorine resistance. Finally, we have further demonstrated that in the FO processes, one can concentrate waste brine while simultaneously harvesting the osmotic energy as electricity, offering potential applications of forward osmosis-based osmotic batteries for powering electronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Mexican-hat potential energy surface in two-dimensional III 2 -VI 3 materials and the importance of entropy barrier in ultrafast reversible ferroelectric phase change

First-principles calculations reveal a Mexican-hat potential energy surface (PES) for two-dimensional (2D) In 2 Se 3 . This unique PES leads to a pseudo-centrosymmetric paraelectric β phase that resolves the current controversy between theory and experiment. We further show that while the α-to-β (ferroelectric-to-paraelectric) phase transition is fast and coherent, assisted by an in-plane shear phonon mode, a random distribution of the atoms in the trough of the PES acts as an entropy barrier against the reverse β-to-α transition. This will be the origin of the speed limitation of current In 2 Se 3 ferroelectric devices. Furthermore, if one orders the β phase (due to the formation of in-plane ferroelectric domains), the reverse transition can take place within tens of picoseconds in the presence of a perpendicular electric field. Finally, the Mexican-hat PES is a general feature for the entire family of 2D III 2 -VI 3 materials. Our finding offers a critical physical picture in controlling the ultrafast reversible phase transition in 2D In 2 Se 3 and other III 2 -VI 3 materials, which will benefit their practical industrial development for advanced ferroelectric devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Stable Glasses of Organic Semiconductor Resist Crystallization

The instability of glassy solids poses a key limitation to their use in several technological applications. Well-packed organic glasses, prepared by physical vapor deposition (PVD), have drawn attention recently because they can exhibit significantly higher thermal and chemical stability than glasses prepared from more traditional routes. We show here that PVD glasses can also show enhanced resistance to crystallization. By controlling the deposition temperature, resistance toward crystallization can be enhanced by at least a factor of ten in PVD glasses of the model organic semiconductor Alq3 (tris(8-hydroxyquinolinato) aluminum). PVD glasses of Alq3 first transform into a supercooled liquid before crystallizing. By controlling the deposition temperature, we increase the glass → liquid transformation time thereby also increasing the overall time for crystallization. Furthermore, we thus demonstrate a new strategy to stabilize glasses of organic semiconductors against crystallization, which is a common failure mechanism in organic light emitting diode devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Surface plasmons induce topological transition in graphene/α-MoO3 heterostructures

Abstract Polaritons in hyperbolic van der Waals materials—where principal axes have permittivities of opposite signs—are light-matter modes with unique properties and promising applications. Isofrequency contours of hyperbolic polaritons may undergo topological transitions from open hyperbolas to closed ellipse-like curves, prompting an abrupt change in physical properties. Electronically-tunable topological transitions are especially desirable for future integrated technologies but have yet to be demonstrated. In this work, we present a doping-induced topological transition effected by plasmon-phonon hybridization in graphene/α-MoO 3 heterostructures. Scanning near-field optical microscopy was used to image hybrid polaritons in graphene/α-MoO 3 . We demonstrate the topological transition and characterize hybrid modes, which can be tuned from surface waves to bulk waveguide modes, traversing an exceptional point arising from the anisotropic plasmon-phonon coupling. Graphene/α-MoO 3 heterostructures offer the possibility to explore dynamical topological transitions and directional coupling that could inspire new nanophotonic and quantum devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Mean-field control for efficient mixing of energy loads

In this work, we pose an engineering challenge of controlling an ensemble of energy devices via coordinated, implementation-light, and randomized on/off switching as a problem in nonequilibrium statistical mechanics. We show that mean-field control with nonlinear feedback on the cumulative consumption, assumed available to the aggregator via direct physical measurements of the energy flow, allows the ensemble to recover from its use in the demand response regime, i.e., transition to a statistical steady state, significantly faster than in the case of the fixed feedback. Moreover when the nonlinearity is sufficiently strong, one observes the phenomenon of “super-relaxation,” where the total instantaneous energy consumption of the ensemble transitions to the steady state much faster than the underlying probability distribution of the devices over their state space, while also leaving almost no devices outside of the comfort zone.

25 ENERGY STORAGE↗
DOE OSTI2024

Reproducible emission from nonlinear random lasers

Multiple scattering of light serves as a mechanism for feedback in random lasers. Consequently, internal spatial mode patterns, lasing wavelengths, and output directionality can all be random. Strong mode interaction can occur in such devices due to spatially overlapping modes resulting in nonlinearity with respect to the pump input power. Nevertheless, temporal coherence and lasing mode amplitude can be fixed at a constant pumping rate. This is a property desirable for applications where unique randomness is exploited but expected to be reliable over time, such as physical unclonable functions. Random lasers can also be cheaply and easily fabricated, exhibit relatively low lasing thresholds and high emission intensity. However, the precise scattering properties of such structures and fluctuations in the pump field can make device emission irreproducible, thereby limiting random laser applications. Here, in this work, we directly compare the random lasing spectra from zinc oxide samples fabricated in four distinct ways: spin-coating, sputtering, solgel deposition, and atomic layer deposition. The particular method of fabrication has a strong impact. Samples made through atomic layer deposition here exhibit both reproducibility and strong nonlinearity desirable for applications. Randomness in emission spectra persists across hundreds of repeated and averaged measurements irrespective of spatial location and is demonstrably nonlinear with respect to input signal intensity.

47 OTHER INSTRUMENTATION↗