SEARCH · Search NASA

Results for “Sensor development”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,549 records · Page 86

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Energy Northwest — Advanced Grid Interactive Load Efficiency (AGILE) : A Techno-economic Assessment

The Advanced Grid Interactive Load Efficiency project team, led by Energy Northwest, was awarded funding as part of the fourth round of the Clean Energy Fund program to investigate, co-create, and complete a preliminary design for grid-interactive efficient buildings (GEBs) for a number of schools served by Grays Harbor PUD. The project team has evaluated different combinations of systems at selected school buildings and the potential to respond to grid and customer needs, and develop a preliminary system technical design, including specifying desired GEB technology options, determining communication and electrical interface requirements, assessing control software sensor requirements, and interfacing with building management systems. PNNL led the techno-economic assessment efforts, leveraging its advanced modeling and analytical methods and tools developed for building-to-grid integration. This report documents the economic assessment for different GEB design options, encompassing an in-depth examination of use cases and value propositions, assumptions and inputs, models, methods, case studies, as well as key findings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2015

Ultrasonic imaging in liquid sodium

The fourth generation of nuclear reactor can use liquid sodium as the core coolant. When the reactor is operating, sodium temperatures can reach up to 600 deg. C. During maintenance periods, when the reactor is shut down, the coolant temperature is reduced to 200 deg. C. Because molten sodium is optically opaque, ultrasonic imaging techniques are developed for maintenance activities. Under-sodium imaging aims at i) checking the health of immersed structures. It should also allow ii) to assess component degradation or damage as cracks and shape defects as well as iii) the detection of lost objects. The under-sodium imaging system has to sustain high temperature (up to 300 deg. C) and hostility of the sodium environment. Furthermore, specific constraints such as transducers characteristics or the limited sensor mobility in the reactor vessel have to be considered. This work focuses on developing a methodology for detecting damages such as crack defects with ultrasound devices. Surface-breaking cracks or deep cracks are sought in the weld area, as welds are more subject to defects. Traditional methods enabled us to detect emerging cracks of submillimeter size with sodium-compatible high-temperature transducer. The presented approach relies on making use of prior knowledge about the environment through the implementation of differential imaging and time-reversal techniques. Indeed, this approach allows to detect a change by comparison with a reference measurement and by focusing back to any change in the environment. It is a means of analysis and understanding of the physical phenomena making it possible to design more effective inspection strategies. Difference between the measured signals reveals the acoustic field scattered by a perturbation (a crack for instance), which may occur between periodical measurements. The imaging method relies on the adequate combination of two computed ultrasonic fields, one forward and one adjoint. The adjoint field, which carries the information about the defects, is analogous to a time-reversal operation. One of the interests of the presented method is that the time-reversal operation is not done experimentally but numerically. Numerical simulations have been carried out to validate the practical relevance of this approach. The preliminary numerical results show a nice agreement between the guessed and the actual positions of the defect. After water-tests, in sodium-tests must be done in order to validate the water/sodium transposition. For this purpose, an under-sodium device is under development, which can move the transducers with four degrees of freedom in a 1.5 m{sup 3} sodium pot. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Monte Carlo Dropout Uncertainty Quantification of Long Short-Term Memory Autoencoder Anomaly Detection in a Liquid Sodium Cold Trap

Advanced high-temperature fluid reactors, such as sodium-cooled fast reactors (SFRs) and molten salt–cooled reactors (MSCRs), require coolant purification systems to prevent fluid contamination and local freezing that can lead to plugging. Liquid sodium purification can be achieved with a cold trap, where the sodium temperature is reduced to a near-freezing point to precipitate out impurities. Automation of monitoring of the cold trap performance with machine learning algorithms can aid in early detection of incipient anomalies. An efficient approach to loss-of-coolant–type anomaly detection in a cold trap monitored with more than two dozen thermal-hydraulic sensors consists of a long short-term memory (LSTM) autoencoder. This work develops the uncertainty quantification of the LSTM autoencoder performance for cold trap anomaly detection using the Monte Carlo (MC) dropout method. The MC dropout methodology creates a distribution of sister distributions that all slightly differ from each other because of random neurons being turned off for testing. The variances of the sister network distributions are used to make an uncertainty interval. Our analysis shows that the uncertainty in the autoencoder performance is largest near the peak of the anomaly signal. Using the MC dropout method, we investigate the uncertainty in the anomaly detection with missing sensor inputs. This capability allows the reactor operator to evaluate resilience of the anomaly detection system and to make informed decisions about continuity of operation in the event of sensor failure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

Tunable optical metamaterial-based sensors enabled by closed bipolar electrochemistry

Enabled by the proliferation of nanoscale fabrication techniques required to create spatially repeating, sub-wavelength structures to manipulate the behavior of visible-wavelength radiation, optical metamaterials are of increasing interest. Here we develop and characterize a chemical sensing approach based on electrochemical tuning of the optical response function of large-area, inexpensive nanoaperture metamaterials at visible and near-IR wavelengths. Nanosphere lithography is used to create an ordered array of sub-wavelength apertures in a Au film. The spacing of these apertures is established during fabrication, based on the size of the polystyrene nanospheres. Tunable shifts in the transmission spectrum can be produced post-fabrication by electrodeposition of a dissimilar metal, Ag, using the nanoaperture film as one electrode in a 2- electrode closed bipolar electrochemical (CBE) cell, altering hole size, film thickness, and film composition while maintaining hole spacing dictated by the original pattern. Optical transmission spectra acquired under galvanostatic conditions can be expressed as a linear combination of the initial and final (saturated) spectra, and the resulting response function exhibits a sigmoidal response with respect to the amount of charge (or metal) deposited. This architecture is then used to perform optical coulometry of model analytes in a CBE-based analyte-reporter dual cell device, thus expanding the capability of CBE-based sensors. Increasing the exposed electrode area of the analyte cell increases the response of the device, while modifying the circuit resistance alters the balance between sensitivity and dynamic range. These tunable nanoaperture metamaterials exhibit enhanced sensitivity compared to CBE electrochromic reporter cells to the μM to nM concentration range, suggesting further avenues for development of CBE-based chemical sensors as well as application to inexpensive, point-of-care diagnostic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Performance Test of Mini LVDT - ELVIS

The Institute for Energy (IFE) Technology has been a pioneer in the development of Linear Variable Differential Transformers (LVDTs) for in-pile testing, deploying over 2,200 units in various reactor environments with less than a 10% failure rate after five years of operation. This report focuses on the performance testing of IFE’s Mini LVDT, a compact sensor ideal for material test reactor experiments. The Mini LVDT, with a limited range of +/- 1.5 mm, offers excellent performance comparable to larger LVDTs, making it valuable in space-constrained applications. The development of an Enhanced Linear Variable Intrinsic Sensor (ELVIS) with internal temperature monitoring capabilities represents a significant advancement, addressing the critical need for real-time, accurate measurements in high-radiation and high-temperature environments. Two ELVIS prototypes were evaluated in terms of both temperature and displacement, showcasing promising results, though challenges with noise during temperature measurements were identified. This report summarizes the rigorous testing performed at Idaho National Laboratory (INL) and highlights the potential applications of Mini LVDTs and ELVIS in nuclear and other high-precision industries.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Leveraging Hydropower Multi-Sensor Data for Inference and Age-Informed Modeling

Increased demand of operational flexibility such as faster ramp up/down in generation, and more frequent start/stops are putting hydropower plants and their associated components in unprecedented stress. Consequently, these plants are at the high risk of extended and more frequent outage to accommodate unscheduled, and unexpected maintenance. Therefore, hydropower plants are in critical need of data driven and age-informed analysis for their regular and unscheduled operation. Yet not all hydropower plants are exhaustively equipped with sensors and/or measurement streams for their respective components – demanding solutions on how to detect, identify, and locate the cause of any event from the unobservable. Idaho National Laboratory (INL) analyzed the anonymized measurements and event records from the Hydropower Research Institute (HRI) to address this issue, as part of the Water Power Technologies Office (WPTO) funded one year multi-lab project. First, we investigated how time series of multiple sensor measurements can be leveraged to identify an event “root cause” as well as to develop an inference (i.e., estimate the unobservable) problem. INL also investigated how individual hydropower components’ reaction or response times vary across the pre-event, during event, and post-event conditions – enabling the hydropower dynamic models to be age-informed. Finally, the impact of clustering multi-sensor time series on short-term vibration prediction is analyzed. INL will present key findings from these analyses and recommend next steps for stakeholder adoption.

13 HYDRO ENERGY↗

DOE OSTI2025

Design, Build, and Initial Testing of a Portable Methane Measurement Platform

The quantification of methane concentrations in air is essential for the quantification of methane emissions, which in turn is necessary to determine absolute emissions and the efficacy of emission mitigation strategies. These are essential if countries are to meet climate goals. Large-scale deployment of methane analyzers across millions of emission sites is prohibitively expensive, and lower-cost instrumentation has been recently developed as an alternative. Currently, it is unclear how cheaper instrumentation will affect measurement resolution or accuracy. To test this, the Wireless Autonomous Transportable Methane Emission Reporting System (WATCH 4 ERS) has been developed, comprising four commercially available sensing technologies: metal oxide (MOx,), Non-dispersion Infrared (NDIR), integrated infrared (INIR), and tunable diode laser absorption spectrometer (TDLAS). WATCHERS is the accumulated knowledge of several long-term methane measurement projects at Colorado State University’s Methane Emission Technology Evaluation Center (METEC), and this study describes the integration of these sensors into a single unit and reports initial instrument response to calibration procedures and controlled release experiments. Specifically, this paper aims to describe the development of the WATCH 4 ERS unit, report initial sensor responses, and describe future research goals. Meanwhile, future work will use data gathered by multiple WATCH 4 ERS units to 1. better understand the cost–benefit balance of methane sensors, and 2. identify how decreasing instrumentation costs could increase deployment coverage and therefore inform large-scale methane monitoring strategies. Both calibration and response experiments indicate the INIR has little practical use for measuring methane concentrations less than 500 ppm. The MOx sensor is shown to have a logarithmic response to methane concentration change between background and 600 ppm but it is strongly suggested that passively sampling MOx sensors cannot respond fast enough to report concentrations that change in a sub-minute time frame. The NDIR sensor reported a linear change to methane concentration between background and 600 ppm, although there was a noticeable lag in reporting changing concentration, especially at higher values, and individual peaks could be observed throughout the experiment even when the plumes were released 5 s apart. The TDLAS sensor reported all changes in concentration but remains prohibitively expensive. Our findings suggest that each sensor technology could be optimized by either operational design or deployment location to quantify methane emissions. The WATCH4ERS units will be deployed in real-world environments to investigate the utility of each in the future.

47 OTHER INSTRUMENTATION↗

DOE OSTI2015

Effects of magnetic field and pressure in magnetoelastic stress reconfigurable thin film resonators

Free-standing CoFe thin-film doubly clamped stress reconfigurable resonators were investigated as a function of magnetic field and pressure. A large uniaxial anisotropy resulting from residual uniaxial tensile stress, as revealed from magnetic hysteresis loops, leads to an easy magnetization axis aligned along the length of the beams. The quality factor of the driven resonator beams under vacuum is increased by 30 times, leading to an enhanced signal-to-noise ratio and a predicted reduction in the intrinsic magnetic noise by a factor of 6, potentially reaching as low as ∼25 pT/√Hz at 1 Torr. Stress reconfigurable sensors operating under vacuum could thus further improve the limit of detection and advance development of magnetic field sensing technology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Develop Wake Mitigation Strategy (CRADA CRD-17-00693 Final Report)

Wind turbines in a wind farm typically operate individually to maximize their own performance and do not take into account information from nearby turbines. In an autonomous wind farm, enabling cooperation to achieve farm-level objectives, turbines will need to use information from nearby turbines to optimize performance, ensure resiliency when other sensors fail, and adapt to changing local conditions. A key element of achieving an autonomous wind farm is to develop algorithms that provide necessary information to ensure reliable, robust, and efficient operation of wind turbines in a wind plant using local sensor information that is already being collected, such as supervisory control and data acquisition (SCADA) data, local meteorological stations, and nearby radars/sodars/lidars. In this work consensus control is applied in a hybrid analysis to data from an existing wind farm to demonstrate the benefit of consensus control.

17 WIND ENERGY↗

DOE OSTI2022

Multi-Sensor Optimal Motion Planning for Radiological Contamination Surveys by Using Prediction-Difference Maps

Distributed and networked mobile sensor platforms using unmanned aerial and/or ground vehicles to survey areas of interest offer a safer and more efficient method for radiological contamination mapping; however, most applications rely on uniformly sweeping of the area in a raster-type motion without utilizing the information available in a dynamic sense. We have developed a fully autonomous optimal motion planning procedure for networks with two or more mobile sensors. The procedure utilizes well-established concepts of Gaussian processes in combination with control laws based on centroidal Voronoi tessellations to achieve optimal next-iteration sensor movements. A new method of informing optimal motion planning is proposed, whereby the absolute difference between the prior and current full-map prediction, referred to as the prediction-difference map, is used as the spatial density function within each Voronoi cell, providing immediate and iterative feedback for dynamic use of available information. The Gaussian process regression model used to estimate the contamination in unvisited locations also provides prediction uncertainties, and can be used as a quantitative metric to assess the confidence in the calculated contamination map; these estimates and prediction uncertainties are unavailable for standard uniform survey routines as they can only produce maps in the vicinity of observed locations. We present through simulation the achievable performance gains from using this new method by directly comparing to a uniform survey method. Results show that using the prediction-difference maps to inform motion planning procedures offers a faster rate of producing an accurate and convergent map relative to a uniform survey route.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Fabrication of Six Degrees-of-Freedom Hexflex Positioner With Integrated Strain Sensing Using Nonlithographically Based Microfabrication

In this study, a process flow is described for the low cost, flexible fabrication of metal micro-electromechanical systems (MEMS) with high performance integrated sensing. The process is capable of producing new designs in ≈1 week at an average unit cost of <$1 k/device even at batch sizes of ≈1–10, with expected sensing performance limits of about 135 dB over a 10 kHz sensor bandwidth. This is a ≈20× reduction in cost, ≈25× reduction in time, and potentially >30× increase in sensing dynamic range over comparable state-of-the-art compliant nanopositioners. The nonlithographically based microfabrication (NLBM) process is uniquely suited to create high performance nanopositioning architectures which are customizable to the positioning requirements of a range of nanoscale applications. These can significantly reduce the cost of nanomanufacturing research and development, as well as accelerate the development of new processes and the testing of fabrication process chains without excess capital investment. A six degrees-of-freedom (6DOF) flexural nanopositioner with integrated sensing for all 6DOF was fabricated using the newly developed process chain. The fabrication process was measured to have ≈30 μ m alignment. Sensor arm, flexure, and trace widths of 150 μ m, 150 μ m, and 800 μ m, respectively, were demonstrated. Process capabilities suggest lower bounds of 25 μ m, 50 μ m, and 100 μ m, respectively. Dynamic range sensing of 52 dB was demonstrated for the nanopositioner over a 10 kHz sensor bandwidth. Improvements are proposed to approach sensor performance of about 135 dB over a 10 kHz sensor bandwidth.

42 ENGINEERING↗

DOE OSTI2019

Thermal Hydraulic Experimental Test Article - Status Report for FY2019 (Rev. 1)

The Thermal Hydraulic Experimental Test Article (THETA) is a facility that will be used to develop sodium components and instrumentation as well as acquire experimental data for validation of reactor thermal hydraulic and safety analysis codes. The facility will simulate nominal conditions as well as protected/unprotected loss of flow accidents in an SFR. High fidelity distributed temperature profiles of the developed flow field will be acquired with Rayleigh backscatter based optical fiber temperature sensors. The facility is being designed in partnership with systems code experts to tailor the experiment to ensure the most relevant and highest quality data for code validation. The design work for the facility has been completed and is currently in the procurement, manufacturing and initial testing stage. The THETA primary system, including the redan, inlet and outlet plenum, 38 kW electric core simulant heater, submerged flowmeter, pump, and all instrumentation has either been procured or is currently being tested at Argonne. The secondary sodium system for cooling the tube-side sodium of the intermediate heat exchanger has all been analyzed according to ASME code and is in the final development stages before procurement.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Journey over Destination: Dynamic Sensor Placement Enhances Generalization

Reconstructing complex, high-dimensional global fields from limited data points is a challenge across various scientific and industrial domains. This is particularly important for recovering spatio-temporal fields using sensor data from, for example, laboratory-based scientific experiments, weather forecasting, or drone surveys. Given the prohibitive costs of specialized sensors and the inaccessibility ofcertain regions of the domain, achieving full field coverage is typically not feasible. Therefore, the development of machine learning algorithms trained to reconstruct fields given a limited dataset is of critical importance. In this study, we introduce a generalapproach that employs moving sensors to enhance data exploitation during the training of an attention based neural network, thereby improving field reconstruction. The training of sensor locations is accomplished using an end-to-end workflow, ensuringdifferentiability in the interpolation of field values associated to the sensors, and is simple to implement using differentiable programming. Additionally, we have incorporated a correction mechanism to prevent sensors from entering invalid regions within the domain. We evaluated our method using two distinct datasets; the results show that our approach enhances learning, as evidenced by improved test scores.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Engineering a new tripartite split-ccGFP system from Corynactis californica for detecting protein–protein interactions

Protein-protein interactions (PPIs) are critical to a range of biological processes and, consequently, aberrant interactions are implicated in many disorders. The study of the complex networks of PPIs promises to elucidate undiscovered roles in cellular processes and the mechanisms of disease. To accomplish this, tools to effectively sense PPIs are necessary. Effective PPI sensors must rapidly detect interactions in real-time with high sensitivity without perturbing the proteins of interest (POIs) under study. Split fluorescent proteins have previously been used to successfully monitor PPIs, in part due to the small size of the tags. Here, we developed an optimized tripartite split GFP system based on Corynactis californica GFP (ccGFP) to detect PPIs in vitro. In this sensor system, ccGFP fragments ccGFP10 and ccGFP11 are tagged to two POIs. PPIs can then be detected via fluorescence by complementation to the third fragment, ccGFP1-9, which reconstitutes functional ccGFP. The optimized ccGFP system shows improved detection kinetics and pH and temperature stability compared to a previous system. We then validated the sensor by monitoring PPIs in two model systems: attractive/repulsive coiled-coils and rapamycin-inducible FRB/FKBP heterodimerization. Finally, we developed an anti-tripartite ccGFP single-chain variable fragment (scFv), which could enable versatile detection of identified protein-protein complexes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Monitoring and Analysis of In-Pile Phenomena in Advanced Test Reactor using Acoustic Telemetry

The interior of a nuclear reactor presents a particularly harsh and challenging environment for both sensors and telemetry due to high temperatures and high fluxes of energetic and ionizing particles among the radioactive decay products. A number of research programs are developing acoustic-based sensing approach to take advantage of the acoustic transmission properties of reactor cores. Idaho National Laboratory has installed vibroacoustic receivers on and around the Advanced Test Reactor (ATR) containment vessel to take advantage of acoustically telemetered sensors such as thermoacoustic (TAC) transducers. The installation represents the first step in developing an acoustic telemetry infrastructure. This paper presents the theory of TAC, application of installed vibroacoustic receivers in monitoring the in-pile phenomena inside the ATR, and preliminary data processing results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

Color-tunable luminescent Ln{sup 3+} composite as self-referencing and ratiometric sensor for low-level water detection in ethanol

Graphical abstract: A new color-tunable luminescent Ln{sup 3+} (Ln = Eu, Tb or Eu and Tb in different molar ratio) composite was prepared through a simple method, which can be applied as self-referencing and ratiometric sensor for detecting low-level water content (0.01-0.5 vol%) in ethanol. - Highlights: • A novel Ln{sup 3+} (Ln = Eu, Tb or Eu and Tb in different molar ratio) complex with tunable luminescence from red to green was prepared through a simple procedure. • The luminescence color of the Eu/Tb co-doped complex can be tuned by water through the luminescence quenching mechanism as well as the variation of energy transfer efficiency from Tb{sup 3+} to Eu{sup 3+}. • The complex with Eu{sup 3+}:Tb{sup 3+} = 1:1 can be applied as self-referencing and ratiometric luminescent sensor for detecting low-content water (0.01–0.5 vol%) in ethanol. - Abstract: Developing simple, fast and sensitive detection of low-level water in organic solvents is in high demand for academic and industrial applications. In this paper, a novel color-tunable lanthanide composite has been prepared by simply mixing 2,2':6',2”-terpyridine-4'-carboxylic acid (Hctpy) and Ln{sup 3+} with a molar ratio of 3:1 in absolute ethanol at room temperature, in which the Ln{sup 3+} ions are mainly coordinated with carboxyl moieties rather than with terpyridine moieties of Hctpy. In addition, the emission colors of the composite can also be tuned by water, ascribed to the luminescence quenching mechanism and the variation of Tb-to-Eu energy transfer efficiency. Based on these properties, a self-referencing and ratiometric luminescent water detector with the Eu/Tb molar ratio of 1:1 has been developed, showing proportional relationship between the intensity ratio of {sup 5}D{sub 0} → {sup 7}F{sub 2} transition of Eu{sup 3+} to {sup 5}D{sub 4} → {sup 7}F{sub 5} transition of Tb{sup 3+} (I{sub Eu}/I{sub Tb}) and the water concentration (0.01–0.5 vol%) in ethanol.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Coaxial printing method for directly writing stretchable cable as strain sensor

Through applying the liquid metal and elastomer as the core and shell materials, respectively, a coaxial printing method is being developed in this work for preparing a stretchable and conductive cable. When liquid metal alloy eutectic Gallium-Indium is embedded into the elastomer matrix under optimized control, the cable demonstrates well–posed extreme mechanic performance, under stretching for more than 350%. Under developed compression test, the fabricated cable also demonstrates the ability for recovering original properties due to the high flowability of the liquid metal and super elasticity of the elastomeric shell. The written cable presents high cycling reliability regarding its stretchability and conductivity, two properties which can be clearly predicted in theoretical calculation. This work can be further investigated as a strain sensor for monitoring motion status including frequency and amplitude of a curved object, with extensive applications in wearable devices, soft robots, electronic skins, and wireless communication.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Remote Sensor Design for Visual Recognition with Convolutional Neural Networks

While deep learning technologies for computer vision have developed rapidly since 2012, modeling of remote sensing systems has remained focused around human vision. In particular, remote sensing systems are usually constructed to optimize sensing cost-quality trade-offs with respect to human image interpretability. While some recent studies have explored remote sensing system design as a function of simple computer vision algorithm performance, there has been little work relating this design to the state-of-the-art in computer vision: deep learning with convolutional neural networks. We develop experimental systems to conduct this analysis, showing results with modern deep learning algorithms and recent overhead image data. Our results are compared to standard image quality measurements based on human visual perception, and we conclude not only that machine and human interpretability differ significantly, but that computer vision performance is largely self-consistent across a range of disparate conditions. This repository contains all the code required to replicate the results of our research paper, and the corresponding docker environment in which that code can be executed. All code is written in Python3 and utilizes the PyTorch library (v1.0) for neural network model training and evaluation. Jupyter notebooks are used to visualize images transformed with our code, in addition to plotting experimental results. We also include the specific parameter files used to execute our experiments, with the intent that these experiments can be replicated.

Zelinski, michaelE.↗