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At least 19 records

DEVELOPMENT OF INEXPENSIVE HIGH TEMPERATURE NITI-BASED SHAPE MEMORY ALLOYS FOR POWDER BED ADDITIVE MANUFACTURING

NiTi and NiTi-based Shape Memory Alloys (SMA) exhibit a reversible solid-state phase transformation from martensite to austenite driven by thermal energy. High temperature (Mf>100°C) SMAs are martensite at room temperature and can be fabricated into solid-state actuators that return to a pre-programmed shape against a designed load after heating to transformation threshold. Reactive as-fabricated additively manufactured parts (4-D printing) is the current state of the art in manufacturing of SMAs but requires compositions compliant to rapid solidification. Existing actuator designs are developed from commercially available, highly investigated material compositions. However, existing high temperature high performance (high actuation strain, low thermal hysteresis) shape memory alloys contain significant (>10% at.) portions of high-cost Platinum Group Metals (PGMs). It is of significant scientific interest to investigate material compositions that are peer performing or superior to PGMs whose constituent elements represent a significant cost savings. Shape memory alloy properties vary significantly with small (0.1% at.) compositional changes making robust investigative sample sets very large. Computational material design can be deployed to shrink the compositional space of possible alloy combinations and reduce the experimental load in material discovery. Investigating shape memory effect (SME) and validating process additive process parameters for a single novel composition is cost intensive in both time and consumed materials. Additionally, sub-optimal processing, oxygen, or solidification rate sensitivity could render additively manufacturing specimens without micro, macro cracks, or significant chemical variance impossible. Unfortunately, such failure susceptibility cannot be simulated. Therefore, a research pathway to validate novel shape memory alloy compositions for powder bed fusion additive manufacturing without the need for powdered feedstock is also proposed. This research investigates novel high temperature shape memory alloys for actuators without platinum group alloying elements to discover one that could be commercially viable as an additive manufacturing feedstock.

Sundermann, Tayler↗

Unsupervised multimodal fusion of in-process sensor data for advanced manufacturing process monitoring

Effective monitoring of manufacturing processes is crucial for maintaining product quality and operational efficiency. Modern manufacturing environments often generate vast amounts of complementary multimodal data, including visual imagery from various perspectives and resolutions, hyperspectral data, and machine health monitoring information such as actuator positions, accelerometer readings, and temperature measurements. However, fusing and interpreting this complex, high-dimensional data presents significant challenges, particularly when labeled datasets are unavailable or impractical to obtain. This paper presents a novel approach to multimodal sensor data fusion in manufacturing processes, inspired by the Contrastive Language-Image Pre-training (CLIP) model. We leverage contrastive learning techniques to correlate different data modalities without the need for labeled data, overcoming limitations of traditional supervised machine learning methods in manufacturing contexts. Our proposed method demonstrates the ability to handle and learn encoders for five distinct modalities: visual imagery, audio signals, laser position (x and y coordinates), and laser power measurements. By compressing these high-dimensional datasets into low-dimensional representational spaces, our approach facilitates downstream tasks such as process control, anomaly detection, and quality assurance. The unsupervised nature of our method makes it broadly applicable across various manufacturing domains, where large volumes of unlabeled sensor data are common. We evaluate the effectiveness of our approach through a series of experiments, demonstrating its potential to enhance process monitoring capabilities in advanced manufacturing systems. This research contributes to the field of smart manufacturing by providing a flexible, scalable framework for multimodal data fusion that can adapt to diverse manufacturing environments and sensor configurations. The proposed method paves the way for more robust, data-driven decision-making in complex manufacturing processes.

Contrastive Learning↗

A Method for Dynamic Kolsky Bar Compression at High Temperatures: Application to Ti-6Al-4V

Abstract An experimental apparatus for measuring the dynamic behavior of materials subjected to strain rates on the order of 10 $$^3$$ 3 s $$^{-1}$$ - 1 and temperatures up to 800°C with a unique triple actuation system is developed in this work. This system is based on the traditional Kolsky (or split-Hopkinson pressure) bar design, with the addition of an external furnace used to heat the specimen to the desired temperature. A synchronized triple pneumatic actuation system is used to control the motion and timing of the the sample, incident, and transmitted bars. The cold contact time (CCT), or the time during which the heated sample is in contact with the room temperature bars before compression, is measured experimentally and carefully controlled to minimize the development of a temperature gradient across the sample and avoid heating of the bars. Experiments are performed in conjunction with ultra high speed imaging and 2D digital image correlation (DIC), as well as high speed thermal imaging. To verify the viability of the proposed system, experiments were conducted on Ti-6Al-4V (wt.%) at temperatures from 25°C up to and 800°C at an average strain rate of approximately 1200 s $$^{-1}$$ - 1 .

36 MATERIALS SCIENCE↗

Steam Generators: Thermal Hydraulic Measurements and Instrumentation

Steam generators are integral components of both conventional and advanced reactors utilizing steam power cycles, as they influence the power conversion performance. Steam generator designs are highly influenced by the type of reactor coolant used, which mainly governs the different control, monitoring, and safety system actuation requirements. Therefore, the present work reviews the thermal hydraulics instrumentation within steam generators designed for pressurized water reactors (PWRs), high-temperature gas-cooled reactors (HTGRs), sodium fast reactors (SFRs), and molten salt cooled reactors (MSRs). Emphasis is given to measurement techniques that are either unique or particularly important to specific reactor types. Lastly, a discussion is provided on the instrumentation and measured parameters. The work identifies standard parameters of interest and is expected to aid the development of test beds and novel measurements techniques.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Specimen sizing and remaining life sample calculations for high temperature reactor material surveillance

Advanced high-temperature nuclear reactors rely on structural components that will operate for decades under combined mechanical, thermal, and environmental loading. Materials surveillance programs are a promising strategy for managing the resulting uncertainty in long-term structural integrity by monitoring degradation in service using passively actuated mechanical test articles. Previous reports have developed a simplified, spreadsheetimplementable framework for sizing these test articles and for inferring accumulated creep damage and remaining life from ex-situ test data. This report advances that work toward practical deployment by providing a sample-problem book: a collection of worked, end-toend examples in which the ASME Section III, Division 5 design analysis of a representative high-temperature reactor component is carried through to a sized surveillance article, verified with detailed finite-element analysis, and concluded with a remaining-life assessment based on an assumed ex-situ creep-rate measurement on the retrieved specimen. The report also summarizes ongoing ANL engagement with ASTM Committee E10 on Nuclear Technology and Applications toward drafting a standard covering surveillance procedures for advanced reactors.

Barua, Bipul (ORCID:0000000247184113)↗

The MuFusE large-volume diamond anvil cell for exploring muon-catalyzed fusion at higher pressures and temperatures

A new large-volume diamond anvil cell (DAC) has been developed for the Muon-catalyzed Fusion (μCF) Experiment (MuFusE), enabling the compression and heating of deuterium–tritium (d–t) mixtures to pressures and temperatures needed to advance μCF research. The MuFusE DAC achieves the large sample volumes necessary for high-precision fusion measurements while integrating cryogenic loading, all-metal sealing, and flexible bellows to maintain a secure environment during cell compression. Combined with remote pneumatic actuation and secondary containment, the DAC safely managed a 25 Ci tritium inventory while providing a clear optical path for in situ measurements of sample pressure and composition via laser spectroscopy. Utilizing 5 mm diameter diamond anvils oriented in the path of a high-intensity muon beam, the apparatus achieved a stable sample volume of 19.2 mm 3 at liquid density, pressures up to 933 MPa and temperatures up to 400 K—benchmarks that significantly exceed previously reported limits for static d–t targets.

Kalow, J. D. [Acceleron Fusion, Inc., Cambridge, M↗

Chemical Compensation Challenges in Processing Antiferroelectric PbZrO 3 Thin Films

The electric field-induced antipolar-to-polar phase transition in antiferroelectric materials is accompanied by large changes in the structural and functional response, making them attractive for many applications ranging from pulsed energy capacitors to high-strain-high (blocking-)force actuators, solid-state heating and cooling systems, and optoelectronic devices. PbZrO 3 , as an end member of the PZT, (x)PbZr 1–x Ti x O 3 , solid solution, has been the subject of many studies. However, processing of perovskite PbZrO 3 is extremely challenging due to phase instabilities induced by Pb loss at the temperatures necessary for perovskite crystallization. Here, we discuss the challenges associated with Pb loss, as well as its compensation through bulk Pb overstoichiometry and interfacial PbO additions, in chemical solution processed, highly oriented PbZrO 3 thin films. For both 042 o - and 001 o -oriented (o-orthorhombic distortion) PbZrO 3 thin films, the crystallization interfaces are the most important contributors to Pb loss and off-stoichiometric outcomes, and no single approach was sufficient to address these challenges. Pb-rich and Pb-deficient nonperovskite phases including ZrO x were only observable through microscopic characterization, and X-ray diffraction alone could not rule out the presence of such secondary phases. “Ideal” macroscopic antiferroelectric polarization-electric field double hysteresis curves were observed despite (at times) the large presence of secondary phases. However, reduced saturation polarization and increased phase transition electric fields were observed concomitantly with the presence of secondary phase(s) and tentatively assigned to the voltage drop across the ZrO x nanocrystals. Based on these results, it is imperative that the presence of secondary phases always be addressed (beyond X-ray diffraction spectra) in order to correctly evaluate the properties of antiferroelectric films.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Divertor-safe nonlinear burn control based on a SOLPS parameterized core-edge model for ITER

Abstract For ITER operations, the range of desirable burning-plasma regimes with high fusion power output will be restricted by various operational constraints. These constraints include the saturation of ITER’s various heating and fueling actuators such as the neutral beam injectors, the ion and electron cyclotron heating systems, the gas puffing system, and the deuterium–tritium pellet injectors. In addition to these actuator constraints, the H-mode power threshold, divertor detachment, and the heat load on the divertor targets may apply limitations to ITER’s operational space. In this work, Plasma Operation Contour (POPCON) plots that map the aforementioned constraints to the temperature-density space are used to investigate which constraints are most limiting towards accessing regimes with high fusion power output. The presented POPCON plots are based on a control-oriented core-edge model that couples the nonlinear density and energy response models for the core-plasma region with SOLPS4.3 parameterizations for conditions in the edge-plasma regions (scrape-off-layer and divertor). Using this control-oriented core-edge model, a nonlinear burn controller, which aims to regulate the plasma temperature and density in the core-plasma region, is constructed in this work. This controller is augmented with an online optimization scheme that governs the control references such that the plasma can be guided towards regimes with high fusion powers while protecting the divertor targets from dangerously high heat loads. A closed-loop simulation study illustrates the capability of this burn control scheme.

Physics↗

Feasible Actuator Range Modifier (FARM), a Tool Aiding the Solution of Unit Dispatch Problems for Advanced Energy Systems

Integrated energy systems (IESs) seek to minimize power generating costs in future power grids through the coupling of different energy technologies. To accommodate fluctuations in load demand due to the penetration of renewable energy sources, flexible operation capabilities must be fully exploited, and even power plants that are traditionally considered as base-load units need to be operated according to unconventional paradigms. Thermomechanical loads induced by frequent power adjustments can accelerate the wear and tear. If a unit is flexibly operated without respecting limits on materials, the risk of failures of expensive components will eventually increase, nullifying the additional profits ensured by flexible operation. In addition to the bounds on power variations (explicit constraints),the solution of the unit dispatch problem needs to meet the limits on the variation of key process variables, including temperature, pressure and flow rate (implicit constraints).The FARM (Feasible Actuator Range Modifier) module was developed to enable existing optimization algorithms to identify solutions to the unit dispatch problem that are both economically favorable and technologically sustainable. Thanks to the iterative dispatcher–validator scheme, FARM permits addressing all the imposed constraints without excessively increasing the computational costs. In this work, the algorithms constituting the module are described, and the performance was assessed by solving the unit dispatch problem for an IES composed of three units, i.e., balance of plant, gas turbine, and high-temperature steam electrolysis. Finally, the FARM module provides dedicated tools for visualizing the response of the constrained variables of interest during operational transients and a tool aiding the operator at making decisions. These techniques might represent the first step towards the deployment of an ecological interface design (EID) for IES units.

47 OTHER INSTRUMENTATION↗

Ink-based laser powder bed fusion of barium titanate

Barium titanate (BTO) is a lead-free functional ceramic that is widely used in sensors, transducers, and actuators. The increasing demand for complex geometries and quick design iterations motivates the use of additive manufacturing techniques. Laser powder bed fusion (L-PBF) additive manufacturing technique enables the net-shape or near-net-shape fabrication of metals and alloys. Ceramic L-PBF remains challenging due to their high melting temperature. Here, to address this challenge, a nanoparticle ink feedstock was incorporated into the L-PBF process to allow low power melting of BTO. Key print parameters (i.e. laser power, scanning speed, and hatching spacing) were optimized to fabricate millimeter-scale BTO parts. The printed BTO samples possessed an inhomogeneous equiaxed-columnar-cellular microstructure. Semiconducting current-voltage behavior was observed in as-printed samples, which was attributed to the creation of oxygen vacancies. The piezoelectric d 33 coefficient was measured to be 4.6 pC/N.

Dielectrics↗

LC-Opt: Benchmarking Reinforcement Learning and Agentic AI for End-to-End Liquid Cooling Optimization in Data Centers

Liquid cooling is critical for thermal management in high-density data centers with the rising AI workloads. However, machine learning-based controllers are essential to unlock greater energy efficiency and reliability, promoting sustainability. We present LC-Opt, a Sustainable Liquid Cooling (LC) benchmark environment, for reinforcement learning (RL) control strategies in energy-efficient liquid cooling of high-performance computing (HPC) systems. Built on the baseline of a high-fidelity digital twin of Oak Ridge National Lab's Frontier Supercomputer cooling system, LC-Opt provides detailed Modelica-based end-to-end models spanning site-level cooling towers to data center cabinets and server blade groups. RL agents optimize critical thermal controls like liquid supply temperature, flow rate, and granular valve actuation at the IT cabinet level, as well as cooling tower (CT) setpoints through a Gymnasium interface, with dynamic changes in workloads. This environment creates a multi-objective real-time optimization challenge balancing local thermal regulation and global energy efficiency, and also supports additional components like a heat recovery unit (HRU). We benchmark centralized and decentralized multi-agent RL approaches, demonstrate policy distillation into decision and regression trees for interpretable control, and explore LLM-based methods that explain control actions in natural language through an agentic mesh architecture designed to foster user trust and simplify system management. LC-Opt democratizes access to detailed, customizable liquid cooling models, enabling the ML community, operators, and vendors to develop sustainable data center liquid cooling control solutions.

Naug, Avisek [Hewlett Packard Enterprise]↗

Active control of laser beam pointing for the Zettawatt-Equivalent Ultrashort pulse laser System: a proof-of-principle study with 16-inch optics

We present a proof-of-principle study of active beam-pointing control for the Zettawatt-Equivalent Ultrashort pulse laser System (ZEUS) using a piezo-actuated 16-inch mirror. To the best of our knowledge, this is the largest actively controlled mirror reported in a high-power laser system. A simple proportional feedback control was implemented based on a field-programmable gate array, which reduced the standard deviation of beam-pointing fluctuations by 91% to 0.075 μrad in the horizontal direction and by 78% to 0.25 μrad in the vertical direction. We also demonstrated the elimination of long-term pointing jitter caused by temperature drift using the same apparatus.

laser pointing control↗

Postirradiation Examination of WIRE-21 Experiment Irradiated in the High Flux Isotope Reactor

Westinghouse Electric Company is developing wireless sensors to monitor the centerline temperature and internal pressure of commercial light-water reactor fuel rods during irradiation. Oak Ridge National Laboratory and Westinghouse Electric Company developed the Wireless Instrumented RB Experiment 2021 (WIRE-21) to test wireless temperature and pressure sensor technologies in a removable beryllium position in the High Flux Isotope Reactor. The experiment was irradiated for a total of 75 days, at temperatures ranging from approximately 150°C to 400°C, resulting in a peak fast (energy > 0.1 MeV) neutron fluence of about 3 × 10 21 n/cm 2 . The temperature was intentionally cycled multiple times to compare the response of the wireless temperature sensor to collocated thermocouples. Similarly, the pressure sensor was actuated in multiple steps to compare the response of the wireless measurement to excore pressure transducers (Petrie et al., 2023). After irradiation, the experiment was disassembled in the Irradiated Fuels Examination Laboratory (IFEL) hot cell at Oak Ridge National Laboratory with the intent to recover sensor and dosimetry components, document the as-irradiated condition of the hardware, and investigate possible causes of the sensor behavior observed during irradiation. The postirradiation examination successfully recovered and preserved key WIRE-21 components. After the housing was removed using a milling machine, the internal experiment sections were examined. All eight fiber-optic sensors were recovered, cut, and stored. The silicon carbide thermometry, temperature sensor, pressure sensor, lower spacer, and selected pressure and temperature cable sections were also removed and stored. The metal bellows of the pressure sensor was found to be plastically deformed, indicating that it had been properly pressurized during irradiation and generally behaved as expected. X-ray diffraction analysis of a section of one of the irradiated inductor cores within the pressure sensor was performed and confirmed the presence of phase-pure alpha ferrite (i.e., no unexpected phase transformations). Inductance testing was performed on the irradiated pressure sensor cores using an unirradiated test coil, and DC resistance measurements of the transceiver coils were also performed. The measurements with irradiated inductor cores assembled inside unirradiated coils showed slightly reduced inductance compared to measurements made with unirradiated cores, but the difference was not sufficient to explain the more significant reductions in inductance that were observed in-pile. Therefore, it is suspected that degradation of the inductor coils (specifically the wire wrapping) is responsible for the reduced inductance observed in-pile.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A simplified approach for creep damage and remaining life calculation for materials surveillance in advanced reactors

High temperature reactor materials will experience a combination of mechanical degradation caused by creep and fatigue and environmental degradation caused by neutron irradiation and, in some cases, exposure to corrosive coolants. A materials surveillance program is one option for ensuring the safe, reliable operation of key reactor components under these conditions. Such a program would monitor the degradation in key material properties over time, using this data to predict how changes in the material properties affect components performance. This could then be used to make plant operational decisions and support eventual plant license extensions. Past work de-scribes such a material surveillance program based on passively actuated mechanical test articles that impose creep-fatigue type loading on test materials driven only by changes in temperature, for example those experienced by components under standard operating cycles. This report focuses on two aspects of the proposed material surveillance program: how to design the test articles to mimic the mechanical response of the corresponding component and how to use ex-situ test data to deter-mine the amount of damaged experienced by the test article (and hence the corresponding compo-nent) in service. Specifically, this report derives and validated simplified methods for both tasks, replacing earlier, more complicated approaches based on simulating the test article response and finding the best specimen design or current damage via complex numerical optimization. The sim-plified methods for each task developed here can be implemented in spreadsheet software and are simple enough for practical use in future operating plants. This report derives the methods (one for sizing and two options for damage inference), verifies the simplified approaches versus more so-phisticated methods, and compares the results of applying the simplified methods to previous re-sults using the complex numerical optimization approach. The report also provides a worked sam-pled problem applying the simplified techniques to a realistic high temperature reactor component.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Ductile Glassy Polymer Networks Capable of Large Plastic Deformation and Heat-Induced Elastic Recovery

Many thermoplastic polymers are ductile by combining strength and large deformations. These deformations are irreversible - known as plastic deformation. Elastomers can deform reversibly but have low strength. To this end, we developed glassy and ductile polyamide networks capable of large plastic deformation (>200% strain) and high strength (~50 MPa tensile strength and ~1500 MPa Young’s modulus), similar to those of polyolefins and Nylon-66. We discovered that hydrogen bonding between meta-phthalamide groups was essential to the ductility. Since these polyamide networks are covalently bonded, we demonstrated their unique durability by repeatable elastic recovery at elevated temperatures, exhibiting indifferent tensile properties in each cycle. Furthermore, when we fixed the strain during the elastic recovery, these polyamide networks actuated stresses of 9–18 MPa, among the highest reported in shape-memory polymer actuators. Here, we envision these ductile, glassy polymer networks as promising alternatives to ductile thermoplastics, given the combined benefit of ductility and durability.

36 MATERIALS SCIENCE↗

Hierarchal structures tuned electrocaloric and electromechanical performance in PVDF-based tetrapolymers

Ferroelectrics with multifunctionalities are gaining increased interest in self-actuated electrocaloric effect (ECE) refrigerators. However, achieving high ECE and electromechanical (EM) coupling concomitantly for maximum heat transfer remains challenging. Here we present the structure-property relationship for poly(vinylidene fluoride-co-trifluoroethylene-co-chlorofluoroethylene-co-double bond), P(VDF-TrFE-CFE-DB), tetrapolymer, which exhibited a high ECE entropy change of 66.5 J Kg −1 K −1 and EM strain of −6.1%. We show that thermal treatment can be a key factor influencing multifunctional properties. High-temperature annealing incorporates DB and CFE units into crystalline grains to form extended-chain crystals, enabling CFE units to induce relaxor behavior and DB units to induce large structural changes at low electric fields. This synergy leads to an enhancement in both ECE and EM performances. Furthermore, at an optimized temperature of 50 °C, the annealed films exhibit giant cross-energy coupling, achieving ECE and EM performances of 100.8 J Kg −1 K −1 and −7.6%. This study provides insights into developing new ferroelectric polymers with electroactive multifunctionalities.

36 MATERIALS SCIENCE↗

Design of a double-sided laser heating compatible piezoelectrically driven dynamic diamond anvil cell

Piezoelectrically driven dynamic diamond anvil cells are generally limited to use at room temperature due to spatial conflicts with the optical components necessary for double-sided laser heating. Here, this work describes the design of a double-sided laser-heating-compatible, piezoelectrically driven dynamic diamond anvil cell (LH-dDAC) that expands the range of experimentally accessible compression rate/temperature space. By developing a spatially in-parallel design, in which the diamond anvils and the piezo actuators lie alongside each other, the total length of the apparatus is reduced to 66.5 mm. The new LH-dDAC is capable of probing both overpressure and compression-rate effects on the kinetics of phase transitions. We illustrate the capability of the new LH-dDAC using the following cases: (1) a simultaneous pressure and temperature jump from 19.5 GPa and room temperature to 40 GPa and ≈1550 K and (2) a controlled compression ramp at ≈1850 K and ≈100 GPa/s. By pairing rapid compression with laser heating, the new LH-dDAC opens the door to studies of diffusionally controlled transformations at high pressures and temperatures.

Copley, J. A. [Princeton Univ., NJ (United States)↗

Impact of various DIII-D diagnostics on the accuracy of neural network surrogates for kinetic EFIT reconstructions

Abstract Kinetic equilibrium reconstructions make use of profile information such as particle density and temperature measurements in addition to magnetics data to compute a self-consistent equilibrium. They are used in a multitude of physics-based modeling. This work develops a multi-layer perceptron (MLP) neural network (NN) model as a surrogate for kinetic Equilibrium Fitting (EFITs) and trains on the 2019 DIII-D discharge campaign database of kinetic equilibrium reconstructions. We investigate the impact of including various diagnostic data and machine actuator controls as input into the NN. When giving various categories of data as input into NN models that have been trained using those same categories of data, the predictions on multiple equilibrium reconstruction solutions (poloidal magnetic flux, global scalars, pressure profile, current profile) are highly accurate. When comparing different models with different diagnostics as input, the magnetics-only model outputs accurate kinetic profiles and the inclusion of additional data does not significantly impact the accuracy. When the NN is tasked with inferring only a single target such as the EFIT pressure profile or EFIT current profile, we see a large increase in the accuracy of the prediction of the kinetic profiles as more data is included. These results indicate that certain MLP NN configurations can be reasonably robust to different burning-plasma-relevant diagnostics depending on the accuracy requirements for equilibrium reconstruction tasks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗