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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Volatile organic compound emissions from 4D printing: Effects of material composition and external stimulus

4D printing of stimuli-responsive materials extends 3D printing by enabling the fabricated structures to transform their shapes and properties over time in response to external stimuli. Numerous research efforts have been dedicated to developing new smart materials, enhancing material printability, and ensuring time-evolving properties. Meanwhile, the use of smart materials and external stimuli in 4D printing has introduced the possibility of air emissions that can potentially deteriorate the indoor air quality at the workplace and pose continuous health hazards to users during the production and use phases. These potential air emissions caused by 4D printing have not yet been assessed in current literature, leading to unknown occupational hazards and human health effects. This study focuses on stereolithography-based 4D printing with constrained thermo-mechanics and builds an emission model to quantify the volatile organic compound emissions from printing, shape programming, and shape recovery stages. The established model mathematically links the emission characteristics with material compositional design and stimuli-response mechanisms. Additionally, shape fixity and recovery abilities are considered to analyze the trade-off between the air emissions and stimuli-response performance of 4D printed parts. Case study results suggest that the methacrylate-based thermo-responsive material with higher glass transition temperature leads to higher air emissions, surpassing the permissible exposure level in the indoor environment. By altering the thermo-temporal conditions, a 61.29% reduction in emission yield can be achieved while ensuring a satisfactory shape memory performance.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Harnessing structural stochasticity in the computational discovery and design of microstructures

This paper presents a deep generative model-based design methodology for tailoring the structural stochasticity of microstructures. Although numerous methods have been established for designing deterministic (periodic) or stochastic microstructures, a systematic design approach that allows the unified treatment of both deterministic and stochastic microstructure design domains has yet to be created. The proposed methodology resolves this issue by learning a unified feature space that embodies diverse structural patterns with continuously varying stochasticity levels. A highly diverse microstructure database is established to incorporate various types of deterministic and stochastic microstructure patterns. A property-aware deep generative model is proposed to learn a unified feature space of the structural characteristics, as well as the relationship between structure features and properties of interest. Autoencoder (AE), Variational Autoencoder (VAE), and Adversarial Autoencoder (AAE) are compared to understand their relative merits in the property-aware learning of the unified feature space. Microstructural designs with tailorable stochasticity and properties are obtained by searching the unified feature space. Multiple design cases are presented to demonstrate the capability of designing microstructures for structural stochasticity and properties. Furthermore, the proposed method is employed to create stochastically graded structures, which manipulate the mechanical behaviors by varying the local stochasticity of the structure.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Relativistic non-thermal particle acceleration in two-dimensional collisionless magnetic reconnection

Magnetic reconnection, especially in the relativistic regime, provides an efficient mechanism for accelerating relativistic particles and thus offers an attractive physical explanation for non-thermal high-energy emission from various astrophysical sources. I present a simple analytical model that elucidates key physical processes responsible for reconnection-driven relativistic non-thermal particle acceleration in the large-system, plasmoid-dominated regime in two dimensions. The model aims to explain the numerically observed dependencies of the power-law index $p$ and high-energy cutoff $\gamma _c$ of the resulting non-thermal particle energy spectrum $f(\gamma )$ on the ambient plasma magnetization $\sigma$ , and (for $\gamma _c$ ) on the system size $L$ . In this self-similar model, energetic particles are continuously accelerated by the out-of-plane reconnection electric field $E_{\rm rec}$ until they become magnetized by the reconnected magnetic field and eventually trapped in plasmoids large enough to confine them. The model also includes diffusive Fermi acceleration by particle bouncing off rapidly moving plasmoids. I argue that the balance between electric acceleration and magnetization controls the power-law index, while trapping in plasmoids governs the cutoff, thus tying the particle energy spectrum to the plasmoid distribution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Quasiparton distributions in massive QED2: Toward quantum computation

We analyze the quasiparton distributions of the lightest 𝜂′ meson in massive two-dimensional quantum electrodynamics (QED2) by exact diagonalization. The Hamiltonian and boost operators are mapped onto spin qubits in a spatial lattice with open boundary conditions. The lowest excited state in the exact diagonalization is shown to interpolate continuously between an anomalous 𝜂′ state at strong coupling, and a nonanomalous heavy meson at weak coupling, with a cusp at the critical point. The boosted 𝜂′ state follows relativistic kinematics but with large deviations in the luminal limit. The spatial quasiparton distribution function and amplitude for the 𝜂′ state are computed numerically for increasing rapidity both at strong and weak coupling, and compared to the exact light front results. The numerical results from the boosted form of the spatial parton distributions, compare fairly with the inverse Fourier transformation of the luminal parton distributions, derived in the lowest Fock space approximation. Our analysis points out some of the limitations facing the current lattice program for the parton distributions.

Lattice field theory↗
DOE OSTI2024

Strong Zero Modes in Integrable Quantum Circuits

It is a classic result that certain interacting integrable spin chains host robust edge modes known as strong zero modes (SZMs). In this Letter, we extend this result to the Floquet setting of local quantum circuits, focusing on a prototypical model providing an integrable Trotterization for the evolution of the XXZ Heisenberg spin chain. By exploiting the algebraic structures of integrability, we show that an exact SZM operator can be constructed for these integrable quantum circuits in certain regions of parameter space. Our construction, which recovers a well-known result by Paul Fendley in the continuous-time limit, relies on a set of commuting transfer matrices known from integrability, and allows us to easily prove important properties of the SZM, including normalizabilty. Our approach is different from previous methods and could be of independent interest even in the Hamiltonian setting. Furthermore, our predictions, which are corroborated by numerical simulations of infinite-temperature autocorrelation functions, are potentially interesting for implementations of the XXZ quantum circuit on available quantum platforms.

1-dimensional spin chains↗
DOE OSTI2021

Nuclear Material Process Modeling at the Y-12 National Security Complex

Dynamic simulation modeling is used at Y-12 to evaluate and forecast nuclear material inventories and production capacities to ensure that future supply can meet mission demand. Model outputs are analyzed by numerous Y-12 organizations and programs and coordinated with NNSA’s Office of Secondary Stage Production Modernization. Data-driven decisions for both short-term and long-term strategic planning for Y-12 mission execution are informed by the model. Dynamic simulation modeling capabilities for Y-12 nuclear material production continue to be expanded and refined.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Growth of Jupiter: Formation in disks of gas and solids and evolution to the present epoch

The formation of Jupiter is modeled via core-nucleated accretion, and the planet's evolution is simulated up to the present epoch. Throughout the phases when the planet acquires most of its heavy-element content, the calculation of solids' accretion accounts for interactions with an evolving disk of planetesimals. The phase of growth from an embryo of a few hundred kilometers in radius until the time when the accretion of gas overtakes solids' accretion was presented by D'Angelo et al., and the same numerical methods are applied here. Those calculations followed the formation for about 4 × 10 5 years, until the epoch when the heavy-element and hydrogen/helium masses were $M_Z ≈ 7.3$ and $M_{XY} ≈ 0.15$ Earth's masses ($M_⊕$), respectively, and $\dot {M} _{XY} ≈ $$\dot {M}_Z$. In this work, the calculation is continued through the phase when $M_{XY}$ grows to equal $M_Z$ , at which age, about 2.4 × 10 6 years, the total mass of the planet is $M_p ≈ 20 M_⊕$. About 9 × 10 5 years later, $M_p$ is approximately $60 M_⊕$ and $M_Z ≈ 16 M_⊕$, three-quarters of which are delivered by planetesimals larger than 10 km in radius. Around this epoch, the contraction of the envelope dictates gas accretion rates a few times 10 –3 $M_⊕$ per year, initiating the regime of disk-limited accretion, whereby the planet can accrete all the gas provided by the disk, and its evolution is therefore tied to disk's evolution. Growth is continued by constructing simplified models of protosolar accretion disks that evolve through viscous diffusion, winds, and accretion on the planet. Jupiter's formation ends after ≈ 3.4–4.2 Myr, depending on the applied disk viscosity parameter, when nebula gas disperses. The young Jupiter is 4.5–5.5 times as voluminous as it is presently and thousands of times as luminous, ~10 –5 $L_⊙$. The heavy-element mass is ≈ 20 $M_⊕$. The evolution proceeds through the cooling and contraction phase, in isolation except for solar irradiation. After 4570 Myr, the age of the solar system, radius and luminosity of the planet are within 10$\%$ of current values, accounting also for uncertainties in the power absorbed from the Sun. During formation, and soon thereafter, the planet exhibits features, e.g., luminosity and effective temperature, that may probe aspects of the latter stages of formation, if observable. These possibly distinctive features, however, seem to disappear within a few tens of Myr.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Regional seismic velocity changes following the 2019 M w 7.1 Ridgecrest, California earthquake from autocorrelations and P / S converted waves

SUMMARY We examine regional transient changes of seismic velocities generated by the 2019 Mw 7.1 Ridgecrest earthquake in California, using autocorrelations of moving time windows in continuous waveforms recorded at regional stations. We focus on traveltime differences in a prominent phase generated by an interface around 2 km depth, associated with transmitted Pp waves and converted Ps waves from the ongoing microseismicity. Synthetic tests demonstrate the feasibility of the method for monitoring seismic velocity changes. Taking advantage of the numerous aftershocks in the early period following the main shock, we obtain a temporal resolution of velocity changes up to 20 min in the early post-main-shock period. The results reveal regional coseismic velocity drops in the top 1–3 km with an average value of ∼2 per cent over distances up to 100 km from the Ridgecrest event. These average velocity drops are likely dominated by larger changes in the shallow materials and are followed by rapid recoveries on timescales of days. Around the north end of the Ridgecrest rupture and the nearby Coso geothermal region, the observed coseismic velocity drops are up to ∼8 per cent. The method allows monitoring temporal changes of seismic velocities with high temporal resolution, fast computation and precise spatial mapping of changes. The results suggest that significant temporal changes of seismic velocities of shallow materials are commonly generated on a regional scale by large events.

58 GEOSCIENCES↗
DOE OSTI2025

Hybrid quantum simulations with qubits and qumodes on trapped-ion platforms

We explore the feasibility of gate-based hybrid quantum computing using both discrete (qubit) and continuous (qumode) variables on trapped-ion platforms. Trapped-ion systems have demonstrated record one- and two-qubit gate fidelities and long qubit coherence times, while qumodes, which can be represented by the collective vibrational modes of the ion chain, have remained relatively unex- plored for their use in computing. Using numerical simulations, we show that high-fidelity hybrid gates and measurement operations can be achieved for existing trapped-ion quantum platforms. As an exemplary application, we consider quantum simulations of the Jaynes-Cummings-Hubbard model, which is given by a one-dimensional chain of interacting spin and boson degrees of free- dom. Using classical simulations, we study its real-time evolution and develop a suitable variational quantum algorithm for ground state preparation. Furthermore, our results motivate further studies of hybrid quantum computing in this context, which may lead to direct applications in condensed matter and fundamental particle and nuclear physics.

Lower-dimensional field theories↗
DOE OSTI2024

Nonperturbative phase diagram of two-dimensional N = ( 2 , 2 ) super-Yang-Mills theory

We consider two-dimensional N = ( 2 , 2 ) Yang-Mills theory with gauge group SU ( N ) in Euclidean signature compactified on a torus with thermal fermion boundary conditions imposed on one cycle. We perform nonperturbative lattice analyses of this theory for large 12 ≤ N ≤ 20 . Although no holographic dual of this theory is yet known, we conduct numerical investigations to check for features similar to the two-dimensional N = ( 8 , 8 ) Yang–Mills theory, which has a well-defined gravity dual. We perform lattice field theory calculations to determine the phase diagram, observing a spatial deconfinement transition similar to the maximally supersymmetric case. However, the transition does not continue to low temperature, implying the absence of a topology-changing transition between black hole geometries in any holographic dual for this four-supercharge theory. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Dynamic Earth Energy Storage: Terawatt-year, Grid-scale Energy Storage Using Planet Earth as a Thermal Battery (GeoTES): Phase I Project (Final Report)

Grid-scale energy storage has been identified by the U.S. Department of Energy’s (DOE) Energy Storage Grand Challenge as a necessary technology to support the continued build-out of intermittent renewable energy resources required to attain a carbon-free energy future. To meet this goal, the 2018 Department of Energy Research and Innovation Act mandated the creation of a comprehensive program to accelerate the development and commercialization of next-generation energy storage technologies. One of numerous energy storage technology options is the storage of excess energy as heated geothermal brine in suitable geologic formations. This concept, known as reservoir thermal energy storage (RTES), geologic thermal energy storage (GeoTES), aquifer thermal energy storage (ATES), etc., relies on the storage of thermal energy in geologic formations for recovery and use in large-scale direct use geothermal (e.g., district heating, industrial processes, etc.) and electrical power generation applications. This thermal energy is derived from excess or waste heat from any high-temperature heat source, such as concentrated solar or from conventional thermal/nuclear generation. As such, RTES can potentially play a significant role in meeting the energy storage shortfall in the coming decades. RTES can provide energy arbitrage through both the storage and production of thermal energy stored in geologic formations for direct use applications and can serve as a source of hot fluids that can be used to generate electricity to support peak demand ramping, thus easing stress on transmission and distribution. This energy storage option has geographic benefits in that energy can be stored locally or regionally depending on the various needs/loads. RTES can also be located across an enormous geographic area, without the need for a traditional hydrothermal resource but where thermal gradients and hydrogeology allow economic exploitation of subsurface heat. The work conducted for this project includes (1) a review of lessons learned from past high-temperature RTES international projects; (2) geochemical experimental investigation and numerical simulations of potential domestic sedimentary reservoirs and (3) development of a thermo-hydrological-mechanical (THM) numerical simulation tool for optimizing formation properties and design parameters to maximize thermal energy storage performance.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Finding ways to reduce nuclear waste: searching for the unknown one step at a time

In my home country, Venezuela, research has been stagnant. Due to the political turmoil and the crisis, many educated people have left the country in search for a better life. This has caused a deficit in any technological and scientific advances, making Venezuela one of the first South American countries to have its rate of publications decline by 29% in 2013. Currently, Venezuela lacks the infrastructure and the means to keep up with the research progress as compared to other countries in South America, such as Brazil. Since coming to the United States (US), and currently working for a national laboratory, the active research environment endorses a wide range of careers and engineering programs that allow researchers to thrive at any given field. Researchers have access to funds and tools to succeed in developing materials for the future. There are 17 national laboratories in the US, and all of these have a different research focus/objective. As examples, Los Alamos National Laboratory and Sandia National Laboratory focus is on national homeland security, weapon science, radiation effects, among others. Argonne National Laboratory focuses on nuclear energy, energy storage, high performance computing, etc. At Idaho National Laboratory (INL) the research focuses on innovating nuclear energy and clean energy resources, critical infrastructure materials, along with fuel cycle solutions to manage, dispose and find ways to recycle current and future radiological waste. Compared to other national laboratories, INL focuses slightly more on applied processes and how nuclear energy can be innovated to next reactor design and technologies. The research being conducted at INL made me apply for a Seaborg distinguished postdoctoral position. For the position itself, the researcher must submit a proposal related to actinide chemistry on a research field area. In this position, 50% of my time will be focused on my own proposal. The proposal that I am working on is focused on the innovation of nuclear energy and fuel cycle recycling, which is why I was mainly interested on working at this national laboratory. To give a bit more context of what my proposal is about, a little bit of background is necessary: After the nuclear fuel (UO2) is used in a reactor, the fuel matrix is then characterized by various fission products (FP). Among these FP (including rare earth elements, alkali/alkaline earths, and actinides), many can potentially be recovered through nuclear reprocessing technologies. In pyroprocessing, the used nuclear fuel undergoes electrochemical dissolution into a molten chloride salt mixture in an electrorefiner. Initially, uranium is reduced onto an inert cathode by applied potentials. However, numerous remaining FPs accumulate in the melt and pose challenges for recovery by an inert electrode, particularly the rare earth elements (e.g., Nd, Gd, Pr, Sm) due to their multivalent oxidation states and tendencies toward side reactions, leading to their dissolution in the electrolyte. These recovery challenges result in inefficiencies and necessitate the continual discarding of the molten chloride salt, thereby generating additional waste. Furthermore, the presence of rare earth elements and other fission products in the molten salt electrolyte alters its physical and chemical properties, affecting both uranium recovery efficiency and the longevity of the molten chloride salt. To improve the recovery efficiency of the FP, specifically rare earth elements, I am investigating the fundamental interactions between rare earth elements in the molten chloride salt and their metallic form. The kinetic pathways and the chemical reactions of these elements will give insights on how the recovery efficiency can be improved. The interactions and speciation of these elements are being studied by spectro-electrochemistry at high temperature environments in quartz and other ceramic materials (e.g., alumina crucibles). Some of the challenges I am facing specifically relates the reactivity of some of these elements with different glass and crucible materials. Although my research focuses on fundamental science, it will benefit the applied process by generating new scientific knowledge and closing the gap for an efficient recycling of the waste: one step at a time.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Condition-Based Maintenance of a Circulating Water System of a Canadian Nuclear Power Plant using Machine Learning and Statistical Tools

Canada Deuterium Uranium pressurized-heavy-water reactors (PHWR) are a type of nuclear power plant that generate clean and reliable energy. The scope of this work is to automate data analysis methodologies to inform a condition-based maintenance strategy of a circulating water system (CWS) of a PHWR. The multiunit CWS provides a continuous supply of water to cool steam condensers, even during transient scenarios, thereby improving the thermal efficiency. This work aims to develop a machine learning (ML) based approach to detect anomalies in heterogeneous data of a CWS in a PHWR to help inform a predictive maintenance strategy. The heterogeneous data include textual and numeric time series data for a PHWR. Natural-language-processing (NLP)-based models are used to analyze textual data contained in work orders and operator logs and an event-timeseries correlation detection method is applied to assist anomalies diagnoses for CWS. An ML model Robust Linear Model (RLM) is also used to remove the seasonal variations in the system variable distributions based on distributions of environmental variables. A machine learning model, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), trained on both original data and data without any seasonal variations will then be used to detect if an anomaly exists. Thus, by moving to an automated methodology to detect, classify, and forecast anomalies, the maintenance strategy would be based on component condition instead of a time-based schedule.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Closed-Form Solutions for the Equations of Motion of the Heavy Symmetrical Top with One Point Fixed

The Equations of Motion (EOM) for the Heavy Symmetrical Top with One Point Fixed are highly non-linear. The literature describes the numerical methods that are used to resolve this Classical system including modern tools i.e. the Runge-Kutta Fourth Order method. It is more difficult to derivate closed-form solutions for the EOM and as mentioned in the literature it is not always possible to find the close-form solution for all the EOM. Fortunately, there are a few examples available that will serve as a guide to move further on in this topic. It is the purpose of this paper to find a methodology that will produce the solutions for a given subset of EOM that fulfill certain requisites. The report is organized as follows: it starts with a very short summary of the literature available on this topic and quickly follows into the derivation of the EOM using the Euler-Lagrange method. The Routhian will be used to reduce the size of the expression. It continues with the formulation of the Classical cubic function (f(u)) through a novel process. The roots of f(u) are of the outmost importance to be able to find the EOM closed-form solution, and once the final roots are selected the general method that will produce the closed-form solutions is presented. Two sets of examples are included to show the validity of the process and comparisons of the results from the closed-form solutions vs. the numerical results for these examples are shown.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Exascale granular microstructure reconstruction in 3D volumes of arbitrary geometries with generative learning

Reconstructing 3D granular microstructures within volumes of arbitrary geometries from limited 2D image data is crucial for predicting the material properties, as well as performances of structural components accounting for material microstructural effects. We present a novel generative learning framework that enables exascale reconstruction of granular microstructures within complex 3D geometric volumes. Building upon existing transfer learning techniques using pre-trained convolutional neural networks (CNN), we introduce several key innovations to overcome the difficulties inherent in arbitrary geometries. Our framework incorporates periodic boundary conditions using circular padding techniques, ensuring continuity and representativeness of the reconstructed microstructures. We also introduce a novel seamless transition reconstruction (STR) method that creates statistically equivalent transition zones to integrate multiple pre-existing 3D microstructure volumes. Based on STR, we propose a cost-effective strategy for reconstructing microstructures within complex geometric volumes, minimizing computational waste. Validation through numerical experiments using kinetic Monte Carlo simulations demonstrates accurate reproduction of grain statistics, including grain size distributions and morphology. A case study involving the reconstruction of a 4-blade propeller microstructure illustrates the method’s capability to efficiently handle complex geometries. In conclusion, the proposed framework significantly reduces computational demands while maintaining high reconstruction quality, paving the way for scalable microstructure reconstruction in materials design and analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A high-order Shifted Interface Method for Lagrangian shock hydrodynamics

Here, we present a new method for two-material Lagrangian hydrodynamics, which combines the Shifted Interface Method (SIM) with a high-order Finite Element Method. Our approach relies on an exact (or sharp) material interface representation, that is, it uses the precise location of the material interface. The interface is represented by the zero level-set of a continuous high-order finite element function that moves with the material velocity. This strategy allows to evolve curved material interfaces inside curved elements. By reformulating the original interface problem over a surrogate (approximate) interface, located in proximity of the true interface, the SIM avoids cut cells and the associated problematic issues regarding implementation, numerical stability, and matrix conditioning. Accuracy is maintained by modifying the original interface conditions using Taylor expansions. We demonstrate the performance of the proposed algorithms on established numerical benchmarks in one, two and three dimensions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Hybrid Parameter Search and Dynamic Model Selection for Mixed-Variable Bayesian Optimization

Herein this article presents a new type of hybrid model for Bayesian optimization (BO) adept at managing mixed variables, encompassing both quantitative (continuous and integer) and qualitative (categorical) types. Our proposed new hybrid models (named hybridM) merge the Monte Carlo Tree Search structure (MCTS) for categorical variables with Gaussian Processes (GP) for continuous ones. hybridM leverages the upper confidence bound tree search (UCTS) for MCTS strategy, showcasing the tree architecture’s integration into Bayesian optimization. Our innovations, including dynamic online kernel selection in the surrogate modeling phase and a unique UCTS search strategy, position our hybrid models as an advancement in mixed-variable surrogate models. Numerical experiments underscore the superiority of hybrid models, highlighting their potential in Bayesian optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Challenges in Continuous In-Field Critical Current Testing of High-Temperature Superconducting Tapes: Thermal and Mechanical Perspectives

High-temperature superconductors (HTS) are essential for ultra-high-field applications requiring exceptional current-carrying capacity under extreme conditions. However, systematic characterization of critical current in long-length conductors remains challenging due to complex thermal, electromag netic, and mechanical interactions during continuous testing. This study reports the development of a continuous in-field magnetization testing system for position-dependent critical current measurement in HTS tapes at 20 K under 7.5 T fields applied normal to the tape plane, enabling identification of performance-limiting regions that could compromise magnet stability. Here, the system addresses two fundamental challenges inherent to cryogenic reel to-reel testing. First, thermal management requires continuous cooling of a moving conductor to 20 K, achieved through liquid nitrogen precooling combined with a 100 W@20 K Gifford McMahon cryocooler. Second, screening currents in high fields generate Lorentz forces that induce twisting, bowing, and potential delamination. To mitigate these risks, we propose mechanical reinforcement and active current density suppression strategies. Numerical simulations using the stream function formulation reveal four primary failure modes: frictional heating at guide interfaces, unstable equilibria causing deformation, transverse current-induced stresses at guide transitions, and unsupported forces in vertical spans. Our mitigation strategies include PTFE coated guides to minimize friction, spring-loaded stabilization mechanisms to maintain tape alignment, controlled pre-heating using the liquid nitrogen thermal jacket to suppress critical current at stress points, and optimized guide positioning to minimize force accumulation. The experimental system is nearing completion, with testing planned to commence within two months. Preliminary validation at 65 K under 0.5 T demonstrates strong correlation between simulation-predicted mechanical instabilities and observed critical current variations during conductor tran sitions through the measurement region. These findings establish a robust foundation for quality assurance protocols essential to next-generation superconducting magnet applications.

Chen, Siwei [Princeton Plasma Physics Laboratory (↗