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At least 325 records · Page 18

Strain to failure measurements of Cr coatings with different processing

Differently processed Cr coatings on Zircaloy cladding were assessed for coating strain to failure. This report includes i) quantification of Cr coating strain to failure for several coating variants, ii) incorporation of high throughput analysis developed utilizing artificial intelligence, and iii) develop a hoop direction coating strain to failure testing approach for high temperatures that doesn’t require digital image correlation strain measurements. Room temperature strain to failure measurements indicated that heat treatment had an impact on strain to failure of the coating, with increasing heat treatment temperature increasing the average strain to failure of the Cr coating.

36 MATERIALS SCIENCE↗

Quantifying Thermal Output of Energetic Materials (LDRD Final Report)

We present the results of an LDRD project, funded by the Nuclear Deterrence IA, to develop capabilities for quantitative assessment of pyrotechnic thermal output. The thermal battery igniter is used as an exemplar system. Experimental methodologies for thermal output evaluation are demonstrated here, which can help designers and engineers better specify pyrotechnic components , provide thermal output guidelines for new formulations, and generate new metrics for assessing component performance and margin given a known failure condition. A heat-transfer analysis confirms that the dominant mode of energy transfer from the pyrotechnic output plume to the heat pellet is conduction via deposition of hot titanium particles. A simple lumped-parameter model of titanium particle heat transfer and a detailed multi-phase model of deposition heat transfer are discussed. Pyrotechnic function, as defined by "go/no-go" standoff testing of a heat pellet, is correlated with experimentally measured igniter plume temperature, titanium metal particle temperature, and energy deposition. Three high-speed thermal diagnostics were developed for this task. A three-color imaging pyrometer, acquiring 100k images per second on three color channels, is deployed for measurement of titanium particle temperatures. Complimentary measurements of the overall igniter plume emission ("color") temperature were conducted using a transmission-grating spectrograph in line-imaging mode. Heat flux and energy deposition to a cold wall at the heat-pellet location were estimated using an eroding thermocouple probe, with a frequency response of ~5 kHz. Ultimate "go/no-go" function in the igniter/heat-pellet system was correlated with quantitative thermal metrics, in particular surface energy deposition and plume color temperature. Titanium metal-particle and plume color temperatures both experience an upper bound approximated by the 3245-K boiling point of TiO 2 . Average metal-particle temperatures remained nearly constant for all standoff distances at T = 2850 K, ± 300 K, while plume color temperature and heat flux decay with standoff—suggesting that heat-pellet failure results from a drop in metal-particle flux and not particle temperature. At 50% likelihood of heat-pellet failure, peak time-resolved plume color temperatures drop well below TiO 2 boiling to ~2000 - 2200 K, near the TiO 2 melting point. Estimates of peak heat flux decline from up to 1 GW/m 2 for near-field standoffs to below 320 MW/m 2 at 50% failure likelihood.

36 MATERIALS SCIENCE↗

An outbreak of renal failure in asian dogs due to s-triazine adulteration of pet food raw material: Analysis of unique, green kidney stones formed as a result

Renoliths were removed at necropsy from dogs that had died from acute kidney injury in Asia in 2004 and submitted to our laboratories for analysis including elemental composition, mass spectrometry, and microprobe analysis. The presence of a mixed s-triazine matrix comprising melamine, cyanuric acid, and ammelide, but no detectable ammeline, was found in the stone samples we analyzed. The unusual and unique green coloration of these stones was determined to be due to the presence of biliverdin. The occurrence of these green stones distinguished the 2004 incident from another incident in 2007 in the USA and other reported cases. The presence of crystals was reported in renal tubules and collecting ducts in both outbreaks, but no stones were reported in the 2007 incident. Here, this difference suggested a variation in the disease process caused by mixed s- triazine ingestion. Careful monitoring of food additives is warranted to prevent future problems in animals and humans.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Advanced Reactor Cyber Analysis and Development Environment (ARCADE) for System-Level Design Analysis

Cybersecurity is a persistent concern to the safety and security of Nuclear Power Plants (NPPs), but has lacked data-driven, evidence-based research. Rigorous cybersecurity analysis is critical for the licensing of advanced reactors using a performance-based approach. One tool that enables cybersecurity analysis is modeling and simulation. The nuclear industry makes extensive use of modeling and simulation throughout the decision process but lacks a method to incorporate cybersecurity analysis with existing models. To meet this need, the Advanced Reactor Cyber Analysis and Development Environment (ARCADE) was developed. ARCADE is a suite of publicly available tools that can be used to develop emulations of industrial control system devices and networks and integrate those emulations with physics simulators. This integration of cyber emulations and physics models enables rigorous cyber-physical analysis of cyber-attacks on NPP systems. This report provides an overview of key considerations for using ARCADE with existing physics models and demonstrates ARCADE’s capabilities for cybersecurity analysis. Using a model of the Small Modular Advanced High Temperature Reactor (SmAHTR), ARCADE was able to determine the sensitivity of the primary heat exchangers (PHX) to coordinated cyber-attacks. The analysis determined that while the PHX’s failures cause disruption to the reactor, they did not cause any safety limits to be exceeded because of the plant design, including passive safety features. Further development of ARCADE will enable rigorous, repeatable, and automated cyber-physical analysis of advanced reactor control systems. These efforts will also help reduce regulatory uncertainty by presenting similar types of cybersecurity analyses in a common format, driving standard approaches and reporting.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Toward Drilling the Perfect Geothermal Well: An International Research Coordination Network for Geothermal Drilling Optimization Supported by Deep Machine Learning and Cloud Based Data Aggregation

The EDGE project, supported by the U.S. Department of Energy Geothermal Technologies Office under award DE-EE0008793, established a data-driven framework for improving the efficiency, cost-effectiveness, and reliability of geothermal well drilling. The project focused on developing scalable data infrastructure, advanced machine learning and probabilistic models, and integrated analytics tools to support continuous drilling optimization. A central objective was to reduce geothermal drilling costs by up to seventy percent while minimizing the risk of well failure through predictive diagnostics and adaptive planning. Over the project period, a comprehensive data repository was designed and deployed, incorporating records from over one hundred geothermal wells across varied geological settings. This repository supported both structured and unstructured data and adhered to FAIR data principles, enabling provenance tracking, quality control, and standardized metadata. The project introduced automated ingestion pipelines and a cloud-hosted platform that facilitated access to raw, processed, and derived datasets. This infrastructure served as the foundation for model development and analysis. Machine learning workflows were developed to predict key drilling metrics including rate of penetration, non-productive time, and total drilling costs. Self-organizing maps and dimensionality reduction methods were used to uncover operational patterns and outliers, while supervised learning algorithms such as random forests and deep neural networks were applied to forecast performance outcomes. The models were validated on heterogeneous datasets from both U.S. and Icelandic fields, demonstrating variable but significant predictive accuracy. The results indicated that finer temporal resolution, inclusion of lithological data, and consistency in operational annotations could substantially improve model performance. The project also implemented process mining techniques to reconstruct state-transition models from drilling event logs. These models enabled the identification of deviations from optimal workflows and provided insights into recurring failure modes. Analysis of non-productive time highlighted the impact of equipment failures, geological challenges, and human factors, offering opportunities for targeted mitigation strategies. The EDGE Dashboard was developed as a web-based expert system integrating data visualization, model outputs, and user-driven queries. It provided an accessible interface for operators to explore historical data, evaluate predicted outcomes, and compare drilling scenarios. Initial feedback from project partners suggested that the dashboard could serve as a foundation for more advanced advisory and optimization tools. Overall, the EDGE project demonstrated the feasibility and value of applying modern data science techniques to geothermal drilling. It delivered a set of interoperable tools and models that can support more efficient, lower-risk well development. The findings point toward a viable path for transitioning from advisory analytics to semi-autonomous drilling systems, contingent on continued collaboration, expanded datasets, and field validation. The project results have immediate relevance for drilling operations, data management practices, and future geothermal R&D efforts aimed at achieving reliable, cost-competitive geothermal energy at scale.

15 GEOTHERMAL ENERGY↗

Hygrothermal aging and recycling effects on mechanical and thermal properties of recyclable thermoplastic glass fiber composites

Abstract Glass fiber‐reinforced polymer composites are widely used in marine applications, including renewable energy devices and submarines, due to their strength‐to‐weight ratios and corrosion resistance. As sustainability becomes more important, recyclable thermoplastic composites are gaining attention in marine energy applications. These materials face harsh conditions such as high chloride water, UV radiation, pressurization, and thermal cycling, which can affect their durability and recyclability. This study examines the impact of hygrothermal aging on the recyclability of an Elium glass fiber (GF) composite. Samples were mechanically ground for recycling, and mechanical and thermal properties were compared between aged and unaged samples. After seawater aging, the tensile strength and modulus of the unaged composite dropped by 25% and 13% respectively, due to water ingress along the fiber‐matrix interface. The recycled composite showed reduced flexural strength as the long fiber composite was converted into short fibers during the process. Differential scanning calorimetry (DSC) revealed no change in glass transition temperature after aging. Weight loss (25%) was attributed to the thermal stability of the glass fibers. Dynamic mechanical analysis (DMA) showed that the storage modulus increased with aging, and fracture analysis confirmed a mixed mode of failure for aged composites. Highlights Hygrothermal aging lowers mechanical performance of Elium® GF composites. Failure mechanism tends to be matrix cracking and interface bonding. Glass transition temperature is not reduced by hygrothermal aging. Fractured composite was successfully recycled via thermoforming. Flexural strength of the recycled composite is lower.

17 WIND ENERGY↗

Degradation in photovoltaic encapsulation strength of attachment: Results of the first PVQAT TG5 artificial weathering study

Delamination of the encapsulant in photovoltaic (PV) module technology results in immediate optical loss and may enable subsequent corrosion or mechanical damage. The effects of artificial weathering were not previously known; therefore, an empirical study was performed to survey the factors most affecting adhesion, including the ultraviolet (UV) source (ie, Xe or fluorescent lamp[s]), the optical filters for the lamp, the chamber temperature, and the relative humidity. Natural weathering was also performed at locations, including the following: Golden, Colorado; Miami, Florida; Phoenix, Arizona; QiongHai, China; Riyadh, Saudi Arabia; and Turpan, China. Specimens were constructed using a laminated glass/poly (ethylene-co-vinyl acetate)/glass geometry. The compressive shear test (CST) was used to quantify the mechanical strength of attachment, taken as a proxy for adhesion. The fractography of select specimens (including cross-sectional optical microscopy) was used to verify the failure mode (delamination or decohesion). Additional analysis of the local solar spectrum as well as the specimen temperature was performed to interpret the results of natural weathering. The goals of this study include to identify the most significant stressors, clarify where strong coupling may occur between stressors, and validate accelerated test results relative to natural weathering. The importance of specimen conditioning (for moisture) and hygrometric degradation as well as the effects of UV degradation are identified in this paper.

14 SOLAR ENERGY↗

Mechanical and Corrosion Assessment of Friction Self-Piercing Rivet Joint of Carbon Fiber-Reinforced Polymer and Magnesium Alloy AZ31B

In the present work, thermoset carbon fiber–reinforced polymer (CFRP) was spot joined to magnesium alloy AZ31B by a friction self-piercing riveting (F-SPR) process. Lap shear tensile and cross-tension testing were used to evaluate the mechanical joint performance. An average lap shear tensile load of 5.18 kN was achieved, while an average of 2.81 kN was found from cross-tension testing. All F-SPR samples showed a pullout of AZ31B after mechanical testing, indicating good mechanical interlocking between the steel rivet and AZ31B. Corrosion potential was measured for each material to establish the galvanic corrosion characteristics. As expected, AZ31B was found to be the most active, while thermoset CFRP was the most noble. The steel rivet fell between the AZ31B (active) and the thermoset CFRP (noble). Salt fog corrosion testing (ASTM B-117) was performed to evaluate the corrosion performance of the uncoated F-SPR joint. With up to 200 h of exposure, the post-corroded F-SPR joint integrity retained 81.2% of the pre-exposure F-SPR joint strength with AZ31B pullout failure mode. From cross-sectional analysis of the F-SPR joint, extensive corrosion of AZ31B was observed at the joint and other exposure areas. However, steel rivet was not significantly corroded due to sacrificial anode effect by which AZ31B corroded first in the galvanic couple.

36 MATERIALS SCIENCE↗

MECHANICAL AND CORROSION ASSESSMENT OF FRICTION SELF-PIERCING RIVET JOINT OF CARBON FIBER-REINFORCED POLYMER AND MAGNESIUM ALLOY AZ31B

In the present work, thermoset carbon fiber–reinforced polymer (CFRP) was spot joined to magnesium alloy AZ31B by a friction self-piercing riveting (F-SPR) process. Lap shear tensile and cross-tension testing were used to evaluate the mechanical joint performance. An average lap shear tensile load of 5.18 kN was achieved, while an average of 2.81 kN was found from cross-tension testing. All F-SPR samples showed pull-out of AZ31B after mechanical testing, indicating good mechanical interlocking between the steel rivet and AZ31B. Corrosion potential was measured for each material to establish the galvanic corrosion characteristics. As expected, AZ31B was found to be the most active, while thermoset CFRP was the most noble. The steel rivet fell between the AZ31B (active) and the thermoset CFRP (noble). Salt fog corrosion testing (ASTM B-117) was performed to evaluate the corrosion performance of the uncoated F-SPR joint. With up to 200 h of exposure, the post-corroded F-SPR joint integrity retained 81.2% of the pre-exposure F-SPR joint strength with AZ31B pull-out failure mode. From cross-sectional analysis of the F-SPR joint, extensive corrosion of AZ31B was observed at the joint and other exposure areas. However, steel rivet was not significantly corroded potentially due to sacrificial anode effect by which AZ31B corroded first in the galvanic couple.

Lim, Yong Chae↗

Report on the Creation and Progress of the Hydrogen Regulatory Research Review Group

The current U.S. nuclear generation fleet is increasingly recognized by governmental, scientific, public policy, and industrial communities as having a strategic role in support of the ongoing national transition to a clean energy future. Federal incentives and actions are aligning to expand the role of nuclear power as a viable and more flexible contributor to the evolving national clean energy mix through programs and initiatives such as nuclear power loan guarantees; the Inflation Reduction Act’s (IRA) clean nuclear electrical, steam, and hydrogen incentives; the Infrastructure Investment and Jobs Act (IIJA, also referred to as the Bipartisan Infrastructure Act or BIL); and near term Department of Energy (DOE) funding opportunities related to nuclear based hydrogen hubs and nuclear integrated hydrogen demonstration projects. . Additionally, leveraging clean nuclear electricity and steam is being explored by industries desiring to transition away from carbon-intensive energy sources. Even with all these emerging enablers, notable barriers remain for the widespread adoption of these opportunities within the U.S. nuclear fleet, including the following: • Assurance of the markets for alternate products needed to support decision-making for large capital modification investments • Electric utility mindset and business history centered solely on producing electricity • Design change complexity and regulatory uncertainty associated with plant modifications needed to support alternate product streams The DOE Light Water Reactor Sustainability (LWRS) Flexible Plant Operations and Generation (FPOG) Pathway is developing options to help U.S. nuclear power plants (NPP) in all these areas to enable NPPs designed for steady baseload operation to integrate with intermittent wind and solar capacity to assure reliable clean energy for the nation. Current and near-term laboratory research is focusing on the technical, regulatory, safety, demonstration, and economic elements in support of improving nuclear plant flexibility through hybrid production of electricity and other non-electric products such as hydrogen and energy arbitrage.

42 ENGINEERING↗

In-situ Detection of Glovebox Glove Degradation Prior to Glove Failure; Effects on Safety, Waste, and Operational Costs - 20402

Glovebox glove pressure decay leak testing and analysis of the data can greatly improve glovebox safety, minimize Transuranic (TRU) glove waste, and minimize operational cost. It is well known, the weakest point of containment on a glovebox is the glove. Mitigating unplanned openings in gloves is critical to minimizing operational and safety costs in glovebox operations. Mitigating unplanned glove openings due to glove failures will be discussed in this paper. The lack of an engineered solution to determine a gloves operational life in nuclear operations, has lead to use of theoretical and manual subjective methods to determine the life and safety of a glovebox glove. Whether the glove is inspected visually prior to use, or gloves are changed regularly to theoretically avoid failure, both the operators PPE and the room are being exposed to contamination, or un-necessary amounts of TRU glove waste are being generated. Millions of dollars yearly in operational costs are spent on glove failures due to loss of production, incident analysis, regulatory audits, clean up, and paperwork. In a nuclear application, a glove failure could contaminate an operator and laboratory, shut down the operation for weeks, potentially create a regulatory audit, and potentially create a media frenzy; the damages to the organization can be astronomical. Elimination of glove failures is possible by tracking glove material degradation and setting limits to allow glove change when it becomes necessary, prior to glove failure. Analytical pressure decay leak testing allows the detection of material degradation, and in turn the ability to limit operational glove failures. A German based company called MK Versuchsanlagen, e.K., has developed an advanced Glove Integrity Testing System. The system, with its use of proprietary RFID and special software technology, is unique in its capabilities. The system is capable to perform highly accurate regular glove testing on any size glovebox line in minimal time. The system records and can analyze a tremendous amount of system data that in turn can determine, for example, a safe glove change time prior to a glove material failure. This paper will show how an advanced Glove Integrity Testing System can detect glove material degradation and help determine a safe change point prior to glove failure. Pressure decay curves of new gloves and recorded effects of accelerated aging on the glove over time will be shown. The use of this technology in nuclear facilities can greatly improve glovebox operational safety, minimize glovebox glove TRU waste, and save organizations tremendous costs in downtime, clean up, documentation, and potential regulatory review. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Full-field quantitative visualization of shock-driven pore collapse and failure modes in PMMA

The dynamic collapse of pores under shock loading is thought to be directly related to hot spot generation and material failure, which is critical to the performance of porous energetic and structural materials. However, the shock compression response of porous materials at the local, individual pore scale is not well understood. This study examines, quantitatively, the collapse phenomenon of a single spherical void in PMMA at shock stresses ranging from 0.4 to 1.0 GPa. Using a newly developed internal digital image correlation technique in conjunction with plate impact experiments, full-field quantitative deformation measurements are conducted in the material surrounding the collapsing pore for the first time. The experimental results reveal two failure mode transitions as shock stress is increased: (i) the first in situ evidence of shear localization via adiabatic shear banding and (ii) dynamic fracture initiation at the pore surface. Numerical simulations using thermo-viscoplastic dynamic finite element analysis provide insights into the formation of adiabatic shear bands (ASBs) and stresses at which failure mode transitions occur. Further numerical and theoretical modeling indicates the dynamic fracture to occur along the weakened material inside an adiabatic shear band. Finally, analysis of the evolution of pore asymmetry and models for ASB spacing elucidate the mechanisms for the shear band initiation sites, and elastostatic theory explains the experimentally observed ASB and fracture paths based on the directions of maximum shear.

42 ENGINEERING↗

Exploring the Performance Boundaries of a Small Reconfigurable Multi-Mission UAV through Multidisciplinary Analysis

The performance of a small reconfigurable unmanned aerial vehicle (UAV) is evaluated, combining a multidisciplinary approach in the computational analysis of additive manufactured structures, fluid dynamics, and experiments. Reconfigurable UAVs promise cost savings and efficiency, without sacrificing performance, while demonstrating versatility to fulfill different mission profiles. The use of computational fluid dynamics (CFD) in UAV design produces higher accuracy aerodynamic data, which is particularly important for complex aircraft concepts such as blended wing bodies. To address challenges relating to anisotropic materials, the Tsai–Wu failure criterion is applied to the structural analysis, using CFD solutions as load inputs. Aerodynamic performance results show the low-speed variant attains an endurance of 1 h, 48 min, whereas its high-speed counterpart is 29 min at a 66.7% higher cruise speed. Each variant serves different aspects of small UAS deployment, with low speed envisioned for high-endurance surveying, and high speed for long-range or time-critical missions such as delivery. The experimental and simulation results suggest room for design iteration, in wing area and geometry adjustments. Structural simulations demonstrated the need for airframe improvements to the low-speed configuration. This paper highlights the potential of reconfigurable UAVs to be useful across multiple industries, advocating for further research and design improvements.

42 ENGINEERING↗

Failure Mechanism Traceability and Application in Human System Interface of Nuclear Power Plants using RESHA

In recent years, there has been considerable effort to modernize existing and new nuclear power plants with digital instrumentation and control systems (DI&C). However, there has also been considerable concern both by industry and regulatory bodies for the risk and consequence analysis of these systems. Of particular concern are digital common cause failures (CCFs) specifically related to software defects. These “misbehaviors” by the software can occur in both the control and monitoring of a system. While many new methods have been proposed to identify potential software failure modes, such as Systems-theoretic Process Analysis (STPA), Hazard and Consequence Analysis for Digital Systems (HAZCADS), etc., these methods are focused primarily on the control action pathway of a system. In contrast, the information feedback pathway lacks unsafe control actions (UCAs), which are typically related to software basic events; thus, assessment of software basic events in such systems is unclear. In this work, we present the idea of intermediate processors and unsafe information flow (UIF) to help safety analysts trace failure mechanisms in the feedback pathway and how they can be integrated into a fault tree for improved assessment capability. The concepts presented are demonstrated in two comprehensive case studies, a smart sensor integrated platform for unmanned autonomous vehicles and another on a representative advanced human system interface (HSI) for safety critical plant monitoring. The qualitative software basic events are identified, and a fault tree analysis is conducted based on a modified Redundancy-guided Systems-theoretic Hazard Analysis (RESHA) methodology. The case studies demonstrate the use of UIF and intermediate processors in the fault tree to improve traceability of software failures in highly complex digital instrumentation feedback. The improved method can also clarify fault tree construction when multiple component dependencies are present in the system.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Failure Mechanism Traceability and Application in Human System Interface of Nuclear Power Plants using RESHA

In recent years, there has been considerable effort to modernize existing and new nuclear power plants with digital instrumentation and control systems (DI&C). However, there has also been considerable concern both by industry and regulatory bodies for the risk and consequence analysis of these systems. Of particular concern are digital common cause failures (CCFs) specifically related to software defects. These “misbehaviors” by the software can occur in both the control and monitoring of a system. While many new methods have been proposed to identify potential software failure modes, such as Systems-theoretic Process Analysis (STPA), Hazard and Consequence Analysis for Digital Systems (HAZCADS), etc., these methods are focused primarily on the control action pathway of a system. In contrast, the information feedback pathway lacks unsafe control actions (UCAs), which are typically related to software basic events; thus, assessment of software basic events in such systems is unclear. In this work, we present the idea of intermediate processors and unsafe information flow (UIF) to help safety analysts trace failure mechanisms in the feedback pathway and how they can be integrated into a fault tree for improved assessment capability. The concepts presented are demonstrated in two comprehensive case studies, a smart sensor integrated platform for unmanned autonomous vehicles and another on a representative advanced human system interface (HSI) for safety critical plant monitoring. The qualitative software basic events are identified, and a fault tree analysis is conducted based on a modified Redundancy-guided Systems-theoretic Hazard Analysis (RESHA) methodology. The case studies demonstrate the use of UIF and intermediate processors in the fault tree to improve traceability of software failures in highly complex digital instrumentation feedback. The improved method can also clarify fault tree construction when multiple component dependencies are present in the system.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Optimal Geometry for Focused Ion Beam-Milled Samples for Direct-Pull Micro-Tensile Testing Performed In Situ in a Scanning Electron Microscope

A thorough procedure was developed to efficiently manufacture dogbone samples using focused ion beam (FIB) milling for micro-tensile testing. A Bruker PI 89 PicoIndenter, Billerica, MA, USA, was used as a case study, although the analysis and results are applicable to other micro-mechanical testing systems capable of mounting a standard, Ø12.7 mm × Ø3.2 mm pin, scanning electron microscopy (SEM) pin stub (Ted Pella, Redding, CA, USA). Nine dogbones were made from an Fe-45Cu alloy additively manufactured using powder-fed laser-directed energy deposition (DED-LB). Testing showed that fracture was confined to the gauge section for all dogbones and that the fracture mode, ductile vs. brittle, was entirely dependent on the grain orientation relative to the loading direction. The analysis showed that the measured plastic strain to failure can vary from >11% (optimal geometry) to <1% (non-optimal geometry) in micro-tensile testing of high-tensile-strength (>1 GPa) metallic materials. Subsequently, a finite element analysis (FEA) was conducted to identify the improved dogbone geometries. A total of ten thousand dogbone geometries were tested, and their dimensions were defined by a set of four adjustable parameters (corner radius, load surface angle, load surface length, and dogbone head length). The gauge width and gauge length were fixed to 4 µm and 10 µm, respectively. Three-dimensional surface plots of the stress concentration as a function of two parameters were used to identify the optimal ranges of parameter values. The addition of maximum width and length constraints, measuring 25 µm and 30 µm, respectively, allowed us to identify an optimal geometry at load surface angles of 30° and 45°. Their respective dimensions (corner radius, load surface length, and dogbone head length) are, in µm, 12, 6, and 7 and 10, 7, and 7. Testing these two optimal geometries with a range of gauge lengths from 4 to 20 µm showed that smaller gauge lengths only slightly reduced the detrimental stress concentration outside the gauge section. However, smaller gauge lengths will notably improve the FIB surface polishing step as tapering is reduced with smaller dogbone lengths.

Chemistry↗

A prediction model of failure threshold for shear deformation in a Zr-based bulk metallic glass

The failure of bulk metallic glasses (BMGs) during plastic deformation at room temperature is abrupt and instantaneous, while the analysis of precursor information based on avalanche events helps predict catastrophic failure. An acoustic emission (AE) signal can provide accurate precursor information for material failure, due to its sensitive and high fast calculation ability. In the current study, AE monitoring tests are carried out during uniaxial compression tests of BMGs at different strain rates. The AE experimental failure threshold, E max , is proposed on the basis of AE cumulative energy, which reflects the intensity of damage evolution at different loading conditions. Compared with the critical shear band velocity (CSBV) associated with stick-slip dynamics of serrated flow, E max is a more sensitive failure parameter since it is connected with the local microscopic changes that occur during the material response process. Here, the E max is obtained prior to reaching the CSBV since the calculation of these two avalanches analysis focuses on the different stages of shear band growth. In particular, AE events are related to the “dry” friction process in the first stage, however, the CSBV is responsible for the “viscous” glide in the second stage. Therefore, Emax is not affected by the complex interactions between the shear bands during the stick-slip process. The maximum avalanche of serrated flow, S max , is proposed as the experimental failure threshold, which depends on the applied strain rate as S max ~ $\dot{ε}$ –λ . According to the relationship of E max and S max , the theoretical failure threshold, E max , follows a criterion E max = 2545$\dot{ε}$ –λ - 4468, where λ is equivalent to 0.15 for this work. Finally, combining the different calculations and AE measurements, this model gives new insights to predict the deformation failure behavior of Zr-based BMGs.

36 MATERIALS SCIENCE↗

Commissioning of the Mu2e Data AcQuisition System and the Vertical Slice Test of the Straw Tracker

The report discusses the commissioning of the DAQ system of the Mu2e experiment. We studied how the tracker works and especially the tracker readout. We used a generator to send pulses and we tried to understand the output and non-output of the DTC, in order to validate the event and run format and all the failure modes. In section one, we describe Charged Lepton Flavour Violation, the main purpose of Mu2e, in section two we describe Mu2e experiment. Section three presents the tracker description and readout, meanwhile section four the DAQ system and event building. In section five, we start explaining the analysis we have done on events and all the failure modes we discovered. In section six, we have done an analysis of the logger and boardreader rate, we validated the generator frequency in section seven and studied the number of hits in function of the channel number in section eight. To conclude we investigated the channel to channel time differences in section nine and in section ten we explain our Monte Carlo simulation, reproducing ROCs readout.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗