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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
NASA NTRS2014

Hybrid Wing Body Model Identification Using Forced-Oscillation Water Tunnel Data

Static and dynamic testing of the NASA 0.7 percent scale Hybrid Wing Body (HWB) configuration was conducted in the Rolling Hills Research Corporation water tunnel to investigate aerodynamic behavior over a large range of angle-of-attack and to develop models that can predict aircraft response in nonlinear unsteady flight regimes. This paper reports primarily on the longitudinal axis results. Flow visualization tests were also performed. These tests provide additional static data and new dynamic data that complement tests conducted at NASA Langley 14- by 22-Foot Subsonic Tunnel. HWB was developed to support the NASA Environmentally Responsible Aviation Project goals of lower noise, emissions, and fuel burn. This study also supports the NASA Aviation Safety Program efforts to model and control advanced transport configurations in loss-of-control conditions.

Murphy, Patrick C.↗
DOE OSTI2023

BISON analysis of FeCrAl and Zircaloy cladding deformation during simulated BWR cyclic dryout conditions

The BISON fuel performance analysis code has been used to study FeCrAl and Zircaloy cladding performance to better understand cladding deformation behavior in boiling water reactors during conditions caused by anticipated operational occurrences (AOOs) or by anticipated transients without scram (ATWS). BISON models of novel separate effects tests simulating ATWS events predicted mechanical responses to thermal cycling boundary conditions. Here, we assessed FeCrAl and Zircaloy deformation and burst models to determine those best suited for cyclic dryout event analysis. In addition, we compared diametral strain profiles of the post-experiment claddings to simulation results. The capability of the BISON code for modeling BWR AOO or ATWS events is promising.

36 MATERIALS SCIENCE↗
NASA NTRS1992

Navier-Stokes turbine heat transfer predictions using two-equation turbulence

Navier-Stokes calculations were carried out in order to predict the heat transfer rates on turbine blades. The calculations were performed using TRAF2D which is a two-dimensional, explicit, finite volume mass-averaged Navier-Stokes solver. Turbulence was modeled using q-omega and k-epsilon two-equation models and the Baldwin-Lomax algebraic model. The model equations along with the flow equations were solved explicitly on a non-periodic C grid. Implicit residual smoothing (IRS) or a combination of multigrid technique and IRS was applied to enhance convergence rates. Calculations were performed to predict the Stanton number distributions on the first stage vane and blade row as well as the second stage vane row of the Rocketdyne Space Shuttle Main Engine (SSME) high pressure fuel turbine. The comparison with the experimental results, although generally favorable, serves to highlight the weaknesses of the turbulence models and the possible areas of improving these models for use in turbomachinery heat transfer calculations.

Ameri, Ali A.↗
NASA NTRS1986

Further shock tunnel studies of scramjet phenomena

Scramjet phenomena were studied using the shock tunnel T3 at the Australian National University. Simple two dimensional models were used with a combination of wall and central injectors. Silane as an additive to hydrogen fuel was studied over a range of temperatures and pressures to evaluate its effect as an ignition aid. The film cooling effect of surface injected hydrogen was measured over a wide range of equivalence. Heat transfer measurements without injection were repeated to confirm previous indications of heating rates lower than simple flat plate predictions for laminar boundary layers in equilibrium flow. The previous results were reproduced and the discrepancies are discussed in terms of the model geometry and departures of the flow from equilibrium. In the thrust producing mode, attempts were made to increase specific impulse with wall injection. Some preliminary tests were also performed on shock induced ignition, to investigate the possibility in flight of injecting fuel upstream of the combustion chamber, where it could mix but not burn.

Morgan, R. G.↗
DOE OSTI2020

Progress Toward Simulating Departure from Nucleate Boiling at High-Pressure Applications with Selected Wall Boiling Closures

Recently, a Eulerian-based two-fluid computational fluid dynamics (CFD) framework with a wall heat flux partitioning approach has been intensively investigated for departure from nucleate boiling (DNB) simulation under the U.S. Department of Energy–funded Consortium for Advanced Simulation of Light Water Reactors (CASL) program. Understanding of the DNB characteristics over a range of pressurized water reactor–like operating conditions and accurate prediction of boiling crisis in the nuclear power system have been grand challenges because of the large impact of DNB on reactor safety and operational economics. The ultimate goal of this task in the CASL program is to introduce a robust multiphase CFD–based DNB modeling framework that is capable of characterizing an entire boiling history in which the wall boiling mode experiences the following through multiple stages of heat transfer mode: (1) single-phase convective heat transfer, (2) nucleate boiling heat transfer, and (3) identification of the departure of nucleate boiling. To validate the CASL boiling model, we have benchmarked simulated DNB over three different flow channel configurations (pipe flow, 5 × 5 fuel bundle with mixing vane tests, and 5 × 5 fuel bundle without mixing vane tests) against experimental measurements, and the validation result with open literature is reported. The DNB detection criteria in the simulation are checked by monitoring the peak wall temperature, wall dryout factor, and net energy balance. In addition to the DNB performance test, some preliminary sensitivity results on closure model selection are reported to address the prediction capability of local void profile against measurements. The boiling simulation tested in this study exhibits a maximum deviation of 24% from the measured DNB value in a high-pressure (i.e., 138 bars) subcooled pipe flow test. The ranges of operating conditions are as follows: 1650 to 2650 kg/m 2 ·s for mass flux and 8.5 to 96 K for subcooled inlet temperature. The deviation is even reduced to 7% when the subcooled temperature is less than 40 K. Besides accuracy, base practice guidelines for DNB detection criteria are tested by monitoring three simulation variables: (1) maximum wall temperature, (2) wall dryout factor (i.e., K-value), and (3) energy balance. Numerical robustness of DNB simulation is largely achieved in most of the validation test except for a few high subcooled test cases.

42 ENGINEERING↗
DOE OSTI2020

Image-driven discriminative and generative machine learning algorithms for establishing microstructure–processing relationships

We investigate methods of microstructure representation for the purpose of predicting processing condition from microstructure image data. A binary alloy that is currently under development as a nuclear fuel was studied for the purpose of developing an improved machine learning approach to image recognition, characterization, and building predictive capabilities linking microstructure to processing conditions. Here, we test different microstructure representations and evaluate model performance based on classification accuracy. A classification accuracy of 95.8% was achieved fordistinguishing between micrographs corresponding to ten different thermo-mechanical material processing conditions.We find that our newly developed microstructure representation describes image data well, and the traditional approachof utilizing area fractions of different phases is insufficient for distinguishing between multiple classes using a relativelysmall, imbalanced original data set of 272 images. To explore the applicability of generative methods for supplementing such limited data sets, generative adversarial networks were trained to generate artificial microstructure images. Two different generative networks were trained and tested to assess performance. Challenges and best practices associated with applying machine learning to limited microstructure image data sets is also discussed. Our work has implications for quantitative microstructure analysis, and development of microstructure-processing relationships in limited data sets typical of metallurgical process design studies.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Demonstration of low-density, high-performance operation of sustained spheromaks and favorable scalability toward compact, low-cost fusion power plants (Final Scientific/Technical Report)

This project worked to advance the technical viability of a novel method for efficiently sustaining stable, high-performance spheromak plasma configurations to serve as the basis of compact, low-cost fusion power plants. In particular, our group worked to improve the method of Steady Inductive Helicity Injection (SIHI) with Imposed-Dynamo Current Drive (IDCD) for spheromak plasma sustainment. Prior to this project demonstrations of this plasma sustainment technology have achieved plasma performance consistent with entry milestone 3 of the BETHE FOA. Research and development (R&D) activities for this project were focused on increasing plasma performance toward a level consistent with exit milestone 4. To do this the PI and his group worked to increase the performance of sustained spheromaks produced in an existing experimental prototype (HIT-SIU) while improving confidence in projections to and design of future, higher performance devices through three primary R&D activities: 1) Improved control over the density of plasma in the device throughout a discharge to provide a pathway for demonstration of spheromaks Ohmically heating to the Mercier beta limit via: a. Fueling the device directly with plasma through the installation of pre-ionized source on the injectors b. Optimization of electrical current waveforms in the driver circuits to enable low-density plasma formation with a lower fueling rate 2) Computational demonstration of a validated, realistic injector circuit coupled to a dynamic plasma model capable of use as a design tool for SIHI drivers and associated circuits for new experimental design points on the pathway to commercial reactors. The improvements in plasma performance achieved during research activity 1), and the computational projections performed in research activity 2) increased the technological readiness level (TRL) of this fusion energy concept toward a level sufficient to attract early-stage private investment and/or other forms of follow-on investment to pursue required R&D activities required for the eventual fusion power plants based on this novel technical approach.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2002

One-Dimensional Spontaneous Raman Measurements of Temperature Made in a Gas Turbine Combustor

The NASA Glenn Research Center is working with the aeronautics industry to develop highly fuel-efficient and environmentally friendly gas turbine combustor technology. This effort includes testing new hardware designs at conditions that simulate the high-temperature, high-pressure environment expected in the next-generation of high-performance engines. Glenn has the only facilities in which such tests can be performed. One aspect of these tests is the use of nonintrusive optical and laser diagnostics to measure combustion species concentration, fuel/air ratio, fuel drop size, and velocity, and to visualize the fuel injector spray pattern and some combustion species distributions. These data not only help designers to determine the efficacy of specific designs, but provide a database for computer modelers and enhance our understanding of the many processes that take place within a combustor. Until recently, we lacked one critical capability, the ability to measure temperature. This article summarizes our latest developments in that area. Recently, we demonstrated the first-ever use of spontaneous Raman scattering to measure combustion temperatures within the Advanced Subsonics Combustion Rig (ASCR) sector rig. We also established the highest rig pressure ever achieved for a continuous-flow combustor facility, 54.4 bar. The ASCR facility can provide operating pressures from 1 to 60 bar (60 atm). This photograph shows the Raman system setup next to the ASCR rig. The test was performed using a NASA-concept fuel injector and Jet-A fuel over a range of air inlet temperatures, pressures, and fuel/air ratios.

Hicks, Yolanda R.↗
DOE OSTI2023

Multifidelity Active Learning for Failure Estimation of TRISO Nuclear Fuel

The Tristructural isotropic (TRISO)-coated particle fuel is a robust nuclear fuel proposed to be used for multiple modern nuclear technologies. Therefore, characterizing its safety is vital for the reliable operation of nuclear technologies. However, the TRISO fuel failure probabilities are small and the computational model is time consuming to evaluate them using traditional Monte Carlo-type approaches. In the paper, we present a multifidelity active learning approach to efficiently estimate small failure probabilities given an expensive computational model. Active learning suggests the next best training set for optimal subsequent predictive performance and multifidelity modeling uses cheaper low-fidelity models to approximate the high-fidelity model output. After presenting the multifidelity active learning approach, we apply it to efficiently predict TRISO failure probability and make comparisons to the reference results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Influence of Proton Activity Gaps between Electrodes on Open-Circuit Potential of H 2 /H 2 and H 2 /Air Cells

Polymer -electrolyte-fuel-cell open-circuit voltages (OCVs) are exactly defined by equation (1), where cathode and anode proton activities [(aH+)cathode and (aH+)anode, respectively] usually are identical, so the third term in the right-hand side of equation (2) is ignored. OCV=E0+RT/2F*ln(a1/2 O2*(a2 H+)cathode/aH2O)-RT/2F*ln((a2 H+)anode/aH2) (1) =E0+RT/2F*ln(a1/2 O2*aH2/aH2O)+RT/2F*ln((a2 H+)cathode/(a2 H+)anode) (2) Water vapor pressure is a colligative property that fundamentally correlates to electrolyte concentrations in aqueous solutions. Proton activity is a function of acid concentration, such as pH, when electrolytes are acids. In polymer-electrolyte membranes, water vapor pressure and acid concentration are understood as relative humidity (RH) and water uptake (λ), respectively, where λ represents number of water molecules per sulfonic acid molecule. Several investigations have reported the relationship between RH and λ, meaning that proton activities and associated water uptakes are intimately related to RH. In actual fuel cell operation, cathode RH is determined by ambient-atmosphere and/or humidifier RH(s), and anode RH depends on hydrogen-circulator RH. Therefore, RH is not always identical at both electrodes, and the difference between electrode RHs is considerable during dry operation of polymer electrolyte fuel cells. Therefore, the third term in the right-hand side of equation (2) may be significant for dry operation. We measured OCVs when hydrogen was supplied to both electrodes at 80°C. One electrode (A) was fixed at 30% RH, while RH at the other electrode (B) was varied (0, 5, 10, 20, and 30%). Measured OCVs varied from 0 to 75 mV. For fuel cell tests, electrode A was supplied with hydrogen at 30% RH; electrode B, oxygen at 0, 5, 10, 20, and 30% RH. OCVs deviated from that measured when RH at electrode B was 30%, increasing from 0 to 60 mV with decreasing RH at electrode B. Results are also shown in Figure 1. Proton activities of both electrodes were thermodynamically calculated. The Gibbs–Duhem relation was applied to obtain molar Gibbs free energies of water and sulfonic acid, and proton activity coefficient was calculated using the Gibbs free energy of sulfonic acid and the relationship between RH and λ1–4, assuming that protons and sulfonic anions show identical ionic-activity coefficients. OCVs were estimated using the third term in the right-hand side of equation (2). Results are shown in Figure 1. Fuel-cell current–voltage performance was poor when RHs at the anode and cathode were 30 and 20%, respectively. To determine kinetic current, we measured the oxygen-reduction reaction (ORR) using a rotating-disk electrode (RDE) in concentrated-acid aqueous solutions, which modeled catalyst-layer ionomers. Kinetic currents decreased with acid concentrations. References T. A. Zawodzinski, Jr., C. Derouin, S. Radzinski, R. J. Sherman, V. T. Smith, T. E. Springer and S. Gottesfeld , J. Electrochem. Soc., 140,1041 (1993) P. K. Das and A. Z. Weber, Proceedings of the ASME 2013 11th Fuel Cell Science, Engineering and Technology Conference, Fuel Cell 18010 (2013) V. A. Sethuraman, J. W. Weidner, A. T. Haug, S. Motupally,b and L. V. Protsailo, J. Electrochem. Soc., 155, B50 (2008) A. Kusoglu and A. Z. Weber, Chem. Rev., 117, 987 (2017) Figure 1

Yoshida, Toshihiko↗
NASA NTRS1993

Generic hypersonic vehicle performance model

An integrated computational model of a generic hypersonic vehicle was developed for the purpose of determining the vehicle's performance characteristics, which include the lift, drag, thrust, and moment acting on the vehicle at specified altitude, flight condition, and vehicular configuration. The lift, drag, thrust, and moment are developed for the body fixed coordinate system. These forces and moments arise from both aerodynamic and propulsive sources. SCRAMjet engine performance characteristics, such as fuel flow rate, can also be determined. The vehicle is assumed to be a lifting body with a single aerodynamic control surface. The body shape and control surface location are arbitrary and must be defined. The aerodynamics are calculated using either 2-dimensional Newtonian or modified Newtonian theory and approximate high-Mach-number Prandtl-Meyer expansion theory. Skin-friction drag was also accounted for. The skin-friction drag coefficient is a function of the freestream Mach number. The data for the skin-friction drag coefficient values were taken from NASA Technical Memorandum 102610. The modeling of the vehicle's SCRAMjet engine is based on quasi 1-dimensional gas dynamics for the engine diffuser, nozzle, and the combustor with heat addition. The engine has three variable inputs for control: the engine inlet diffuser area ratio, the total temperature rise through the combustor due to combustion of the fuel, and the engine internal expansion nozzle area ratio. The pressure distribution over the vehicle's lower aft body surface, which acts as an external nozzle, is calculated using a combination of quasi 1-dimensional gas dynamic theory and Newtonian or modified Newtonian theory. The exhaust plume shape is determined by matching the pressure inside the plume, calculated from the gas dynamic equations, with the freestream pressure, calculated from Newtonian or Modified Newtonian theory. In this manner, the pressure distribution along the vehicle after body expansion surface is then determined. The aerodynamic modeling, the engine modeling, and the exhaust plume analysis are described in more detail. A description of the computer code used to perform the above calculations is given and an input/output example is then given. The computer code is available on a Macintosh floppy disk.

Chavez, Frank R.↗
DOE OSTI2023

Develop and Connect TRISO Failure Analysis and Uncertainty Quantification to Fission Product Release Calculation Capability

The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel cycle systems. This program has been providing engineering-scale support for the development of BISON, a high-fidelity and high-resolution fuel performance tool. Stress-based failure probability has been developed and analyzed to assess the integrity of tri-structural isotropic (TRISO) fuel particles during fuel life cycles. While simple, stress-based approaches to failure probability leveraging the Weibull statistical distribution entails a number of drawbacks when stress concentration occurs near crack tips, including finite element mesh size dependency. In this report, we use an interaction integral approach to the computation of stress intensity factors in functionally graded materials (FGM) for axisymmetric models. The inner pyrolytic carbon (IPyC) cracking induced silicon carbide (SiC) failure is one of the dominated failure modes in TRISO failure analysis. In this study, we consider a crack in the IPyC layer perpendicular to the SiC layer. The interface between these two TRISO layers is considered to be porous, which we simulate considering a transition of mechanical properties over the porous length. These aspects are considered in the computation of stress intensity factor (SIF) from a fracture mechanics approach and compared with the known stress-based failure probability approach.

42 ENGINEERING↗
DOE OSTI2024

ACS Spotlight: Bipolar Membranes for Electrochemical Energy Conversion, Chemical Manufacturing, and Separations

Sustainable energy conversion, chemical manufacturing, and separations are central to addressing the world’s energy and environmental challenges. Electrochemical platforms stand as a cornerstone in addressing these challenges because they are low exergy and can be powered on renewable electrons. In electrochemical systems, bipolar membranes (BPMs) are emerging as a unique class of ion exchange membranes poised to revolutionize various electrochemical processes via pH control of anode and cathode chambers and in situ pH adjustment. In this Spotlight Review, we provide a comprehensive review of electrochemical platforms utilizing BPMs for energy conversion (water electrolyzers for hydrogen production, fuel cells, and flow batteries), chemical manufacturing (electrolyzers that convert carbon dioxide into value-added chemicals and nitrate into ammonia), and separations. The motivation for using BPMs, as well as their performance and durability, in electrochemical platforms are disseminated. We also discuss current challenges that impede BPM electrochemical systems from competing with state-of-the-art electrochemical systems using monopolar ion-exchange membranes (e.g., anion/hydroxide exchange membranes and cation/proton exchange membranes). Here, the review also covers molecular modeling and continuum modeling efforts to understand the basic mechanisms that govern BPM performance.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Modeling ablator defects as a source of mix in high-performance implosions at the National Ignition Facility

Recent indirect drive inertial confinement fusion implosions on the National Ignition Facility (NIF) [Spaeth et al., Fusion Sci. Technol. 69, 25 (2016)] have crossed the threshold of ignition. However, performance has been variable due to several factors. One of the leading sources of variability is the quality of the high-density carbon (HDC) shells used as ablators in these experiments. In particular, these shells can have a number of defects that have been found to correlate with the appearance of ablator mix into the hot spot and a degradation in nuclear yield. These defects include pits on the ablator surface, voids in the ablator bulk, high-Z debris from the Hohlraum wall that adheres to the capsule surface, and finally the inherent granular micro-structure of the crystalline HDC itself. This paper summarizes high-resolution modeling of each of these mix sources in two recent high-performance NIF implosion experiments. The simulated impact from a range of individual capsule defects is found to be broadly consistent with the trends seen in experiment, lending credence to the modeling results and the details of the mixing process that they reveal. Interestingly, modeling of the micro-structure inherent to HDC shows that this perturbation source results in considerable mixing of the deuterium–tritium fuel with ablator material during the implosion. The reduction in fuel compression from this mix results in an approximately factor of two reduction in neutron yield in current implosions and emphasizes the importance of mitigating this significant performance degradation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2004

Crash Simulation of a Boeing 737 Fuselage Section Vertical Drop Test

A 30-ft/s vertical drop test of a fuselage section of a Boeing 737 aircraft was conducted in October of 1999 at the FAA Technical Center in Atlantic City, NJ. This test was performed to evaluate the structural integrity of a conformable auxiliary fuel tank mounted beneath the floor and to determine its effect on the impact response of the airframe structure and the occupants. The test data were used to compare with a finite element simulation of the fuselage structure and to gain a better understanding of the impact physics through analytical/experimental correlation. To perform this simulation, a full-scale 3-dimensional finite element model of the fuselage section was developed using the explicit, nonlinear transient-dynamic finite element code, MSC.Dytran. The emphasis of the simulation was to predict the structural deformation and floor-level acceleration responses obtained from the drop test of the B737 fuselage section with the auxiliary fuel tank.

Fasanella, Edwin L.↗
DOE OSTI2022

Recurrent neural networks for short-term and long-term prediction of geothermal reservoirs

Accurate prediction of geothermal reservoir responses to alternative energy production scenarios is critical for optimizing the development of the underlying resources. While the conventional physics-based models offer a comprehensive prediction tool, data-driven models provide an efficient alternative to build fit-for-purpose predictive models by extracting and using the statistical patterns in the collected data to make predictions. The recurrent neural network (RNN) is a data-driven model that is commonly applied to predict time series sequences. This paper presents a variant of RNN that also utilizes the efficiency of convolutional neural networks (CNN) for the prediction of energy production from geothermal reservoirs. Specifically, a CNN–RNN architecture is developed that takes historical well controls as input (features) and their corresponding production response data as output (labels) to learn an input-output mapping that can predict the future well production responses/performance for any given future well control inputs. The model is paired with a labeling scheme to handle real field disturbances that create data gaps. In addition to the model structure, we introduce a thorough workflow for applying the model, which includes data pre-processing, feature selection, as well as different training strategies for short-term and long-term prediction. Finally, the performance and accuracy of the model are evaluated by applying it to multiple datasets, including a field reservoir model.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Purification of U from U-10Mo scrap generated during the fabrication of high performance research reactor fuel

A low enriched U-Mo alloy fuel is under development to replace highly enriched U fuels currently used in United States high performance research reactors. The alloy casting and fuel fabrication processes will generate scrap streams containing low enriched U (LEU) which must be recovered. Solvent extraction processes were designed using the Argonne Model for Universal Solvent Extraction (AMUSE) to purify solutions containing 20 and 50 g/L U. The feed for the solvent extraction processes was prepared from solutions generated from the dissolution of U-10Mo-Zr foils and U-10Mo-Zr-Al mini-plates. The U purification processes were demonstrated using two, 16-stage banks of miniature mixer-settlers. The solvent extraction experiments demonstrated that all design objectives for the U purification processes could be met. The U recovery in the product stream for each flowsheet was ≥99.9%. The flowsheet demonstrations also showed that the purity of the U Product will meet the requirements of the ASTM International C1462-21 specification for LEU metal enriched to less than 20% 235 U. In conclusion, the AMUSE modeling for both flowsheet demonstrations was validated by comparing predicted and measured concentrations of U, Mo, and Zr in the exit streams and stage samples at steady-state conditions in the mixer-settlers.

modified PUREX process↗
DOE OSTI2022

PFLOTRAN Development FY2022

The Spent Fuel & Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Spent Fuel & Waste Disposition (SFWD) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). A high priority for SFWST disposal R&D is to develop a disposal system modeling and analysis capability for evaluating disposal system performance for nuclear waste in geologic media. This report describes fiscal year (FY) 2022 accomplishments by the PFLOTRAN Development group of the SFWST Campaign. The mission of this group is to develop a geologic disposal system modeling capability for nuclear waste that can be used to probabilistically assess the performance of generic disposal concepts. In FY 2022, the PFLOTRAN development team made several advancements to our software infrastructure, code performance, and process modeling capabilities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗