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At least 19 records

Coordinated Thermal Safety Attack and Defense on EV Battery Management Systems

Battery temperature sensor and battery current sensor data which are key sensing inputs to the Battery Management Controllers in electric vehicles, are vulnerable to possible cyber/ physical manipulation due to known vulnerabilities inherited from CAN bus technology that is used for in-vehicle communications between electronic control units that transfer sensing and control data. In this paper, we first create a simulation that enables us to evaluate impact of cyber physical attacks on electric vehicle battery management system in a controlled environment that violates thermal safety. Specifically, we emulate a Level 3 - DC fast charging system with SAE J1772/CCS, integrated with standard charging controls and thermal safety controls on EVs, and various sensing data flows. Second, we propose a coordinated current and battery temperature attack that has crippling economic, and safety impacts. Third, we quantify the usability, economic and safety impacts of such attacks as a function of the extent of data manipulation. Finally, we propose a physics model driven detection technique to detect presence of such attacks.

25 ENERGY STORAGE

Rolling Root Mean Square Based Multimodal Anomaly Detection for Real Time Monitoring of Smart Grid

Reliable real-time monitoring is valuable for maintaining the operational integrity of modern electrical smart grids. Deployment of heterogeneous sensing technologies in substations has enabled high-resolution, multichannel waveform monitoring, but also introduces challenges for anomaly detection due to noise, baseline drift, and modality-dependent signal characteristics. In this work, we present a computationally efficient unsupervised method for multimodal event detection based on Rolling Root Mean Square based Event Detection (RRMSED). The method is developed using in-house, field deployed sensors collecting data at a utility substation. The sensing system comprises voltage and current sensors, triaxial accelerometers, and magnetometers, collectively capturing electrical, vibrational, and magnetic waveform measurements at high temporal resolution. RRMSED operates by extracting rolling RMS energy features and their first-order temporal differences from consecutive waveform segments for each channel and then applying channel-specific statistical thresholds learned from historical data. A persistence-based exceedance logic is employed to robustly identify transient events while suppressing impulsive noise, and to provide precise temporal localization with high resolution. The framework is designed for continuous server-side operation and can be deployed in real time without requiring complex models. Experiments on simulated waveform data with known ground truth demonstrate low false positive (FP) and false negative (FN) rates. Application to real substation data shows RRMSED to identify events that are not captured by conventional monitoring indicators including fast transient detection algorithm currently deployed in the system. These results indicate that rolling RMS based features provide an effective and practical basis for real-time multimodal event detection in smart-grid substations.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)

Ten questions concerning low-cost indoor air quality sensors: Perspectives from research and practice

Low-cost indoor air quality (IAQ) sensors are increasingly being used in homes and commercial and public buildings, driven by growing concerns about the impact of air on health, cognitive performance, and occupant wellbeing. These sensors offer a potentially transformative opportunity to increase spatial and temporal coverage of IAQ monitoring at a fraction of the cost of conventional reference instruments. However, their widespread use raises questions around accuracy, calibration, placement, data handling and interpretation, and integration into existing standards and workflows. This paper presents ten critical questions concerning the use of low-cost IAQ sensors in buildings, drawing on the latest empirical research, field deployments, and emerging practice. It discusses potential frameworks for deployment and evaluation, examines current sensor capabilities for measuring common pollutants, identifies methodological gaps in validation and uncertainty quantification, and outlines the extent to which existing IAQ standards can accommodate sensor-based evidence. The paper also explores how monitoring needs and deployment models vary by building type, the potential of real-time IAQ data to support building operations, and the ethical and legal implications of widespread sensor use. While significant challenges remain in ensuring data quality and building stakeholder trust, new applications are emerging through open data initiatives and advances in analytics and visualization. As the technology, science, and standards co-evolve, low-cost IAQ sensors are poised to become integral to routine building operation, building science, and environmental health research.

Parkinson, Thomas

Embedding Fiber Optic Sensors in Stainless Steel using Spark Plasma Sintering for Structural Health Monitoring in Harsh Environments

Embedded fiber optic sensors such as fiber Bragg gratings (FBGs) offer a unique route for distributed real-time in-situ imaging of various engineering parameters for numerous purposes. This study advanced the current sensor embedding approaches by exploring a spark plasma sintering (SPS)-assisted technology to embed FBGs in high-temperature structural materials and demonstrated the capability of temperature measurement. In this approach, single-mode FBGs were integrated into stainless steel (SS) 316L components using SPS, followed by the evaluation of the bonding quality between the FBGs and matrix, the optical attenuation of the fibers induced by embedding, and the sensing characters of the FBGs under temperature stimuli. The results demonstrated that superior bonding was achieved between the FBGs and highly-densified SS316L. Examination of the behavior of Bragg gratings validated signal fidelity after embedding. Real-time thermal imaging under temperature cycling using the FBGs demonstrated the effectiveness of the technique for smart materials manufacturing.

36 - MATERIALS SCIENCE

Combining quantum noise reduction resources: A practical approach

Optomechanical sensors are capable of transducing external perturbations to resolvable optical signals. A particular regime of interest is that of high-bandwidth force detection, where an impulse is delivered to the system over a short period of time. Exceedingly sensitive impulse detection has been proposed to observe very weak signals like those due to long-range interactions with dark matter that require much higher sensitivities than current sensors can provide. Quantum resources to go beyond the traditional standard quantum limit of these sensors include squeezing of the light used to transduce the signal, backaction evasion by measuring the optimal quadrature, and quantum nondemolition (QND) measurements that reduce backaction directly. These methods have been developed in the context of gravitational wave detection for target frequencies in the audio band range. Here, we provide the theoretical limits to quantum noise reduction for higher and broader frequency targets, such as those from dark matter signals, while combining quantum-enhanced readout techniques based on squeezed light and QND measurements with optomechanical sensors. Here, we demonstrate that backaction evasion through QND techniques dramatically reduces the technical challenges presented when using squeezed light for broadband force detection, paving the way for combining multiple quantum noise reduction techniques for enhanced sensitivity in the context of impulse metrology.

Optomechanics

Electric Vehicle Charging Data Falsification Attacks Utilizing Behavioral Models

A charging station (CS) and its associated electric vehicle supply equipment (EVSE) and charging electric vehicle (EV) interactions are potential targets for data falsification attacks since CSs are typically unmanned public facilities that are connected to the internet and EVs incorporate the vulnerable CAN bus network, which are both susceptible to remote attacks. The research question being addressed is how is the EV owner and CS negatively affected by CAN bus EV battery current sensor and battery temperature sensor data falsification attacks. Negative effects include economic losses from reduced life span of the battery, battery thermal runaway and fire (and potential loss of surrounding structure), and reduced utilization of the CS due to delayed departure time (longer charging times).

25 ENERGY STORAGE

SMM parallel battery operation in orbit

A parallel battery system for the SMM spacecraft is described. The battery system performance as a function of lifetime over orbit was evaluated. The following equipment performance specifications were examined during a typical orbit: battery current and discharges, voltage limitations, battery temperature variations, and current sensor performance. Tabulated battery performance data is also included.

Broderick, R.

Passive Temperature Sensors for Nuclear Applications

In April 2007, the Department of Energy (DOE) designated the Advanced Test Reactor (ATR) a National Scientific User Facility (NSUF) to advance US leadership in nuclear science and technology. By attracting new users from universities, laboratories, and industry, this program supports basic and applied nuclear research to help address the nation's energy security needs. In support of this program, the Idaho National Laboratory (INL) established in-house capabilities to develop, fabricate, test, and qualify new and enhanced temperature sensors for irradiation testing. This effort is continuing today through the DOE?s Advanced Sensors and Instrumentation (ASI) program. Although most efforts emphasize sensors capable of providing real-time data, selected tasks have been completed to enhance passive sensors for irradiations where instrumentation leads cannot be included. These sensors include silicon carbide (SiC) monitors, melt wires and the sublime temperature monitor. SiC monitors are available to detect peak irradiation temperatures between 200°C and 800°C in reactor locations where instrumentation leads cannot be used. SiC monitors may be evaluated using specialized equipment installed at INL?s Measurement Sciences Laboratory (MSL). A melt wire inventory is also maintained at MSL. This inventory contains wires for specific use in irradiation experiments ranging in temperatures from 30°C to 1500°C. Melt wires and SiC monitors have had decades of research and application. Recent research has produced a passive monitor known as the sublime temperature monitor. This passive sensor has the capability of recording temperature gradients. This paper will discuss passive temperature sensors currently being researched and implemented under the ASI program.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS

Assessing the limitations of commercial sensors and models for supporting marine carbon dioxide removal monitoring: a case study

Several unknowns remain surrounding marine Carbon Dioxide Removal (mCDR) monitoring, reporting, and verification (MRV) practices and capabilities. Current in-situ sensor technology is limited (primarily pH and pCO 2 ), requiring calculations and assumptions to estimate changes in carbonate chemistry parameters, including total alkalinity (TA). Considering that cost, energy consumption, and accuracy of commercial sensors can vary by orders of magnitude, understanding how well existing sensors perform in an mCDR context is important for this emerging community. Likewise, documenting sensor limitations and how relatively simple models can optimize sensor deployments will improve MRV efforts and support protocol development. Here we (1) compare performance a variety of commercially available sensors in a blind mesocosm experiment simulating ocean alkalinity enhancement (OAE), and how sensor performance impacted carbonate chemistry estimates; (2) evaluate if sensors can distinguish the OAE signal from natural variability during a small scale OAE field test in Sequim Bay, WA, USA, and (3) use an idealized ocean biogeochemistry model to explore optimal sensor network design based on (1) and (2). Our mesocosm results indicate that correctly constraining pH uncertainty will be critical for accurate TA estimates with current sensor technology compared to the less impactful variation caused by uncertainty in pCO 2 (pH data that are presented throughout are reported on the total scale (pH T ) unless otherwise noted). Our pilot field test demonstrated that sensors were capable of distinguishing mCDR signatures from natural variability under optimal real-world conditions. Idealized modeling simulations of the field test showed that a range of sparse and dense (3 to 100) sensors sampling areas of detectable increases will underestimate the net change in surface pH by at least 35–55%, at both realistic and highly elevated alkalinity input levels. We also highlight the limitations of current sensing technology for MRV, and the importance of ocean biogeochemistry models as critical tools for predicting when and where mCDR signals will be detectable using available sensors. Overall, our findings suggest that commercially available pCO 2 sensors and some pH sensors will form an important backbone for mCDR MRV tasks, though complete MRV characterization will require these data to be used in combination with other tools.

OAE

Integration Methods for High-Density Integrated Electric Drives (Final Technical Report)

The project goal was to research, design and fabricate high-power-density, high-performance SiC power electronic modules for motor drive inverters in electric vehicles (EVs) to enable the subsequent motor drive to achieve a power density of 100 kW/l. EVs use electric motors instead of internal combustion engines as the prime mover, and their core components are semiconductor-based power electronic modules. Efficient power electronic modules play a vital role in power conversion systems. The performance of power modules directly affects the energy efficiency and overall performance of electric vehicles. Therefore, it is particularly important to develop power modules with high power density and high electrical performance that will perform reliably under EV environmental conditions. To achieve these goals, advanced electronic packaging technologies are required. This report describes a 5-year effort to integrate key aspects surrounding the basic power devices into the module itself to increase power density. These include sensing and sensing readout circuits, gate driver circuits, and two-sided cooling solutions.

33 ADVANCED PROPULSION SYSTEMS

High Precision, High Frequency Printed Antennas

An emerging trend in advanced manufacturing is printed electronics and sensors. The ability to print customized electronics and sensors integrated into functional packages is a growing need within a variety of growing markets such as smart manufacturing, internet of things (IoT), and the small satellite industry. Both Oak Ridge National Laboratory (ORNL) and the MITRE Corporation have seedling research efforts evaluating the potential for future printed electronic systems. High frequency, wide-bandwidth phased array antennas (i.e. >45 GHz) open the door to new applications. However, such sensors require currently prohibitively small feature sizes for commercial 3D printing technologies along with increasing challenges with connecting the driving electronics to such features. An additional finding with related advanced manufacturing challenges is the rapid production of 3D additive connectors for integration with commercial printed circuit boards (PCBs), primarily for advanced in-circuit inspection techniques. This work is developing additive manufacturing processes for producing connected and conductive fine scale 3D features. The primary focus was on aerosol-jet printing (AJP), which has a small minimum resolution (<50 µm) but is traditionally printed flat with small height/width aspect ratios <<1, and developing controls to enable fully 3D, high aspect ratio, and unsupported features. In Phase 1 of this effort, baselines of process performance were characterized, and test coupons produced for both ultra-high frequency antennas and microstructures to support reverse engineering of PCBs. In Phase 2, these efforts will be extended for system demonstration of ultra-high frequency antenna arrays, as well as reverse engineering circuitry for dense PCBs.

42 ENGINEERING

Passive Remote Sensing of Stratospheric and Mesospheric Winds

A passive infrared sensor is described for remote sounding of the wind field in the stratosphere and mesosphere from near Earth orbital spacecraft. The instrument uses gas correlation spectroscopy together with electro-optic phase modulation techniques to measure winds in the 20- to 120-km altitude range globally, both in the day and at night, and with a vertical resolution of better than the atmospheric scale height. Measurement of temperature and the amounts of key atmospheric species may also be made simultaneously and in coincident fields of view with the wind observations. The sensor is currently being developed at the Jet Propulsion Laboratory as a candidate for the upcoming NASA Earth Observation System.

Daniel J Mccleese

Advancing Temperature Monitoring of the Bottom Anode in a Direct Current Electric Arc Furnace Operations with Distributed Optical Fiber Sensors.

The bottom anode in the Direct Current Electric Arc Furnace (DC EAF) is critical for completing the electrical circuit necessary for sustaining the arc within the furnace. For pin-type bottom anodes, monitoring of the temperature of select pins instrumented with thermocouples is performed to track bottom wear in the EAF and inform the operator when the furnace should be removed from service. Furthermore, this work presents the results from a plant trial using distributed temperature monitoring of bottom anode pins in a 165-ton DC EAF over a two-month service period utilizing two optical fiber sensing techniques: fiber Bragg grating (FBG) and Rayleigh backscattering (RBS). The early detection of temperature anomalies along the length of the anode pin through distributed sensing enhances operational safety, providing a robust alternative to traditional thermocouples.

42 ENGINEERING

Diagnostics: Chapter 8 of the special issue: on the path to tokamak burning plasma operation

This chapter presents the activity conducted by the ITPA topical group (TG) on Diagnostics over about the last 15 years. Following a general introduction of the ITER Diagnostics led by their measurement roles, the document is organized in several subchapters detailing the design support, research and development activity conducted by each of the specialist working groups (WGs) of the TG. Please note that the magnetic diagnostics were supported at the TG without a specific WG. Their status is included in the general introduction. In the following some highlights of the subchapter’s contents are provided. Recent advances in ITER first wall (FW) diagnostics for the measurements of plasma-metallic wall interaction in support of the ITER research plan are reported. An InfraRed imaging Video Bolometer for ITER has been developed and tested on several tokamaks to measure the radiated power loss. A laser-induced breakdown spectroscopy (LIBS) technique which utilizes a pulsed laser beam to ablate locally by forming a crater, will measure local tritium inventory in the FW material. Real-time Residual Gas Analyzers will measure the neutral gas composition in a divertor port and an equatorial port during plasma operation. Due to the full metallic FW environment, the plasma-wall interaction in ITER will face several challenges such as the compromised radiated power and divertor heat flux measurements by reflection. Ray tracing and analysis codes have been developed to eliminate and correct the effects of reflection in the measurements. The characteristics of the reflecting surfaces depending on the roughness and angle of the incidence have been measured by dedicated experiments, and the results were applied to the reflection elimination. For the measurement of the metallic impurity radiation induced by eroded metallic atoms, a vacuum ultraviolet spectrometer has been developed and tested. An extensive thermonuclear diagnostic suite will be required to support the operation of ITER and the planned experimental program for future burning plasma experiments. Due to the harsh environmental conditions, the implementation of diagnostic systems in ITER is a major challenge. These conditions include high levels of neutron and gamma fluxes, neutron heating, particle bombardment. Therefore, the selection and design of diagnostic systems must take into account a number of phenomena previously unseen in diagnostic design. For this reason, the measurement of neutrons and confined or lost fast ions, with particular emphasis on alpha particles, is critical to ITER. The diagnostics associated with these measurements will be important for future plasma-burning experiments at ITER. The high neutron emission and very large plasma size in ITER make neutron diagnostics the main diagnostic method used to measure plasma parameters such as fusion power, fusion power density, ion temperature, energy of fast ions and their spatial distributions in the plasma core. Active spectroscopy techniques are methods where a neutral particle beam is injected into the plasma and information on plasma parameters is extracted from the measurement of line emission resulting from the beam-plasma interaction, either by plasma ions or by beam atoms. Spatial localization is achieved by crossing the beamline and multiple observation lines. The ITER plasma will be a high temperature, moderately dense, fully ionized collisional plasma. The plasma facing surfaces are principally metallic being fashioned from beryllium or tungsten but many other elements, arising from either structural or from operational needs, may enter this plasma. The energy range of the emitted photons range from meV (infra-red) to multi keV (x-rays) and originate from all areas of the plasma volume. The primary role of passive emission diagnostics is to identify what is in the plasma from spectral signatures. Extracting quantitative information from these measurements such as impurity content, ion temperature, rotation, degree of detachment and radiated power depends on calibrated instruments, a physics model of the atomic and molecular processes and plasma transport and an analysis workflow that takes into account environmental effects such as reflections. The particular needs for ITER have prompted a multi-machine, many-year effort to address all these aspects and this chapter reviews the work on diagnostic design, experiments and new analysis techniques. An overview of the laser diagnostics to be implemented on ITER is also provided in this paper. This includes descriptions of the Thomson scattering in the core, edge and divertor regions, polarimetry and interferometry diagnostics used for measuring plasma density and also measurements of helium density in the divertor using Laser Induced Flourescence. Techniques which can allow improvements on current measurements are also addressed in particular expanding poloidal polarimetry measurements to measure field fluctuations and proposed use of dispersion interferometery which has a number of advantages over existing methods. This paper identifies particular areas where further research and testing on existing tokamaks is useful even at this advanced stage to inform the design of diagnostics for ITER. Outstanding areas of concern for the implementation of laser diagnostics, in particular with a view to reliable operation are identified. An overview of the latest developments of microwave diagnostic systems and techniques is given. The primary focus is the contributions for ITER—the next step burning plasma experiment—which is supplemented by describing recent progress of techniques applicable for fusion experiments beyond ITER. The contributions are intentionally kept concise, and are being supplemented by a rich list of references for further studies. Radiation induced effects are receiving continuous and well-deserved attention of the ITER diagnostic community and they are in many cases one of the primary design drivers of the ITER diagnostic systems. The paper summarizes recent progress in this area focusing primarily on the ITER diagnostics but in some cases provides also outlook for the possible solutions for even more demanding radiation environment of fusion reactors beyond ITER. Despite advancements in the area of modeling and simulation of various radiation induced effects, experimental testing in a nuclear environment as close as possible to the target one is still seen as unavoidable for proper qualification of particular diagnostic functional elements. Recent advancement within three diagnostic areas: optical diagnostics, magnetics and bolometers is covered. Encouraging results on qualification of silica glass vacuum window assemblies are presented. In the area of magnetic sensors, progress of irradiation tests performed on ITER in-vessel LTCC inductive sensors is presented with outlook for novel technological approaches to inductive sensors utilizing thick printing and photolithography technologies being highlighted. Summary of advancements in the area of steady state magnetic field sensors based on Hall effect is given. New results of neutron irradiation test of the ITER borosilicate glass inserts for vacuum electrical feedthroughs are summarized finding negligible swelling at target level of neutron fluence. Off-line irradiation tests of fiber optic current sensors for plasma current measurement demonstrated that both for gamma doses up to 5 MGy and a total neutron fluence up to 10 15 cm −2 , radiation induced changes are still compatible with required measurement accuracy on ITER. The ITER bolometers are given as an example how considering radiation effects may influence the diagnostic design. Finally, outlook for future main R&D directions is outlined. All optical and laser-based diagnostics in ITER will be using mirrors to guide plasma radiation toward detectors, cameras and sensors. In the hostile plasma, radiation and particle environment the optical characteristics of diagnostic mirrors will degrade directly affecting the entire performance of involved diagnostic systems. An assessment of factors affecting mirror performance is provided. Among the prime adverse factors are deposition of plasma impurities, sputtering of mirror surface and steam ingress in the vicinity of mirrors. Within the International Tokamak Physics Activity with active support by ITER central team and domestic agencies, the structured research and development (R&D) program on mitigation of risks for diagnostic mirrors is underway. Within this program the mirror material development, the passive mitigation of mirror degradation by using diagnostic ducts and shutters along with an active mirror recovery program comprising the in-situ mirror cleaning and calibration is underway. Recent developments in diagnostic mirror R&D are described in this Chapter along with an example of their implementation of R&D solutions in ITER Infrared Thermography diagnostic. An assessment of still open engineering and physics questions, considerations on mirror risks during an early phase of ITER operation are given along with an overview of diagnostic mirror evolution in the late ITER operation stage toward the demonstration fusion power plant. Several crucial areas of diagnostic R&D outlined in ITER Research Plan are addressed. The basic control groups in a fusion reactor can be broken-down in five categories: (1) plasma position, magnetic configuration, and plasma current control, (2) profile control and confinement optimization, (3) MHD control and suppression, (4) edge dissipation control, radiation and plasma exhaust control and (5) break-down optimization. These categories are coupled via the physics (a control action in one domain will affect the other domains) and via shared actuators (e.g. ECRH for impurity accumulation avoidance, current density distribution control and MHD suppression). Consequently, a supervisory control system should determine the priority of the various control tasks, their couplings, and the interfaces with the safety and interlock system. For the systematic development of the various controllers taking the complexity of the plasma and the control system into account, a model-based approach is required. A short historical overview is given of the developments in systems and control theory and control engineering with special emphasis on those developments that are most relevant for Nuclear Fusion research and operation. An overview is given of the state of the field of fusion plasma control for the control categories. It will be shown how synthetic diagnostics are being developed in ITER and how they are used in diagnostic design and design validation and how they can be in model-based controller synthesis using relatively simple models. In modern control methods, multiple diagnostics are used to constrain relatively simple models. The constrained models provide an estimate for the state. This opens the route to state controllers, such as model predictive control. A major challenge in nuclear fusion research is the coherent combination of data from heterogeneous diagnostics and modeling codes for machine control and safety as well as physics studies. Measured data from different diagnostics often provide information about the same subset of physical parameters. Additionally, information provided by some diagnostics might be needed for the analysis of other diagnostics. A joint analysis of complementary and redundant data allows, e.g. to improve the reliability of parameter estimation, to increase the spatial and temporal resolution of profiles, to obtain synergistic effects, to consider diagnostics interdependencies and to find and resolve data inconsistencies. Physics-based modeling and parameter relationships provide additional information improving the treatment of ill-posed inversion problems. A coherent combination of all kind of available information within a probabilistic framework allows for improved data analysis results. The concept of integrated data analysis (IDA) in the framework of Bayesian probability theory is outlined and contrasted with conventional data analysis. Components of the probabilistic approach are summarized and specific ingredients beneficial for data analysis at fusion devices are discussed.

ITER

High-resolution in-beam video rate imaging with the ClearXCam for synchrotron beamlines

The ClearXCam detector is a new video rate imaging in-beam monitor based on a diamond sensor. Imaging with 2304 effective pixels is achieved by sequentially biasing one of 48 metal stripes on one side of a diamond sensor, while reading out the current from 48 stripes on the other side of the sensor. This system was characterized for real-time X-ray beam diagnostics at synchrotron beam­line 17-BM at the National Synchrotron Light Source II. Significant results include: detection of in-beam structure via the imaging mode, beam focusing in one minute with real-time imaging feedback during a focusing event, linearity over five orders of magnitude, validation of a fast mode operating at 100 Hz, and sub-micron beam-positioning resolution. The system is now available commercially.

36 MATERIALS SCIENCE

In-Situ Process Monitoring Evaluation and Demonstration using Advanced Characterization with Laser Powder Bed Systems

Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) worked with EOS Group to evaluate the current in-situ sensor capabilities of an EOS M290 Laser Powder Bed Fusion machine. The M290 was fitted with a 1 Mega-Pixel (MP) grayscale visible-light camera and a 5 MP temporally integrated (TI) near-infrared (NIR) camera. One print from stainless steel (SS) 316 and two from Inconel 625 (IN625) were performed where data including in-situ imaging and a machine log file were captured. These data were subsequently analyzed using a Dynamic Multi-Scale Segmentation Convolutional Neural Network (DMSCNN) trained on user defined classes and correlated to as-printed flaws, in the form of porosity, discovered in X-Ray Computed Tomography (XCT). In Phase I, two indications were detected in-situ and spatially correlated to stochastic lack-of-fusion flaws discovered using XCT. In Phase II, using these links from in-situ signatures to XCT flaw populations, a second neural network (NN) was trained to create a Voxelized Property Prediction Model (VPPM) to predict porosity percentages within the part using only features garnered from the in-situ data from two IN625 complex geometries. The VPPM was able to accurately predict porosity values for IN625 parts with an R 2 value of 0.764.

36 MATERIALS SCIENCE

In-Situ Process Monitoring Evaluation and Demonstration using Advanced Characterization with Laser Powder Bed Systems

Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) worked with EOS Group to evaluate the current in-situ sensor capabilities of an EOS M290 Laser Powder Bed Fusion machine. The M290 was fitted with a 1 Mega-Pixel (MP) grayscale visible-light camera and a 5 MP temporally integrated (TI) near-infrared (NIR) camera. One print from stainless steel (SS) 316 and two from Inconel 625 (IN625) were performed where data including in-situ imaging and a machine log file were captured. These data were subsequently analyzed using a Dynamic Multi-Scale Segmentation Convolutional Neural Network (DMSCNN) trained on user defined classes and correlated to as-printed flaws, in the form of porosity, discovered in X-Ray Computed Tomography (XCT). In Phase I, two indications were detected in-situ and spatially correlated to stochastic lack-of-fusion flaws discovered using XCT. In Phase II, using these links from in-situ signatures to XCT flaw populations, a second neural network (NN) was trained to create a Voxelized Property Prediction Model (VPPM) to predict porosity percentages within the part using only features garnered from the in-situ data from two IN625 complex geometries. The VPPM was able to accurately predict porosity values for IN625 parts with an R 2 value of 0.764.

36 MATERIALS SCIENCE

Thermal Studies of CMS High-Granularity Calorimeter (HGCAL) Cassettes for the HL-LHC Upgrade

The CMS High Granularity Calorimeter (HGCAL) is a key endcap upgrade for the High-Luminosity LHC, designed to operate in an environment of extreme radiation and high particle rates. Each HGCAL cassette integrates silicon and scintillator modules, front-end ASICs, and a copper cooling plate that provides both mechanical integrity and thermal coupling using two-phase CO₂ cooling. Stable and uniform temperature control is essential to ensure reliable performance of the front-end electronics and to limit radiation-induced leakage currents in the silicon sensors. We present results from thermal characterization studies of pre-series HGCAL cassettes assembled and tested at Fermilab. Embedded RTD/PT1000 temperature sensors were used to measure gradients across copper cooling plates, module layers, and cassette edges under powering conditions representative of operation. The measured thermal behavior demonstrates effective heat transport through the cassette stack and highlights small but systematic variations correlated with geometry and assembly tolerances. These results validate the cooling performance of HGCAL cassettes.

Wang, Jinglu [Northwestern U.]