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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Effects of forest structural and compositional change on forest microclimates across a gradient of disturbance severity

Forest structural diversity and community composition are key in regulating forest microclimates. When disturbance affects structural diversity or composition, forest microclimates may be altered due to changes in soil temperature, soil water content, and light availability. It is unclear however which structural or compositional components, when changed or to what extent, result in microclimatic change. To address this question, we used data from a large scale, manipulative stem-girdling experiment in northern, lower Michigan—the Forest Resilience and Threshold Experiment (FoRTE). FoRTE follows a factorial design with multiple levels of disturbance severity (0, 45, 65, 85%) based on targeted reductions in gross leaf area index via stem-girdling induced mortality. These disturbance severity treatments are applied in two ways: either as top-down (largest trees are killed) or bottom-up (small to medium trees killed) treatments. We examined how multiple components of structural diversity and community composition changed as a product of disturbance severity and type, and then tested for resulting effects on forest microclimates (light availability, soil temperature, and soil water), using a multivariate, Random Forest framework. We found that measures of community composition (species richness, species evenness, and Shannon-Wiener Diversity Index) and stand structure (basal area, standard deviation of DBH, tree size diversity) declined more following disturbance than did measures of canopy cover, heterogeneity, arrangement, or height. However, when changes in each variable from pre- to post-disturbance, measured as log change, were employed in a multivariate, Random Forest regression framework, structural diversity measures of heterogeneity (rugosity, top rugosity), cover (canopy cover), and arrangement (porosity) were the most influential variables, but with differences among bottom-up and top-down treatments We found that the death of large trees from disturbance impacts soil temperature, water, and light environments more substantially and uniformly across disturbance gradients than does the death of smaller trees. Furthermore, our results have implications for both statistical and process-based modeling of forest disturbance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

NDT System for Metal Components in Concrete Structures

The goal of this SBIR program is to develop new NDT technology based on the innovative use of magnetic sensors designed specifically for ECT (Eddy Current Testing) of steel reinforcements in concrete structures. The Phase IIA goal is to expand the R&D accomplished in Phase II, such that the probe system is more capable, and the inspection system is more flexible.

42 ENGINEERING↗
DOE OSTI2020

Stochastic Analysis for Long Term Capital Structures, Systems, and Components Refurbishment and Replacement

As commercial Nuclear Power Plants (NPPs) pursue extended plant operation in the form of Second License Renewal (SLR), opportunities exist for these plants to provide capital investments to ensure long-term safe and economic performance. At the current time, several utilities have announced an intention to pursue extended operation for one or more of their NPPs via SLR . The goal of this research is to develop a risk-informed approach to evaluate and prioritize plant capital investments made in preparation for, and during the period of, extended plant operations to support decisions for NPP operations. Since the capital investments are influenced by various factors, such as markets, safety and regulatory, the decision-making process of NPP operations should take into account relevant factors for balancing risks, costs and profits. The traditional method of capital budgeting is based on the priority list of candidate projects using economic measures such as benefit-investment ratio, net present value (NPV) and internal rate of return. In the literatures, the problem of capital budgeting or the variant can be represented by an appropriate knapsack problem. The knapsack approach to capital budgeting takes as input as investment, along with the cost and profit of each project. The objective of capital budgeting is to find the combination of the binary decisions for every investment such that the overall profit is as large as possible. The output is a collection of projects to be carried out, and we refer this selected collection of projects as a project portfolio. One limitation of traditional optimization models for capital budgeting is that they do not account for risk/uncertainty in profit and cost streams associated with individual projects, they do not account for risk in resource availability in future years [1,2,3]. Projects can incur cost over-runs, especially when projects are large, performed infrequently, and when there is risk regarding technical viability, external contractors, and/or suppliers of requisite parts and materials. Occasionally, projects are performed ahead of schedule and with cost savings. Planned budgets for capital improvements can be cut and key personnel may be lost. Or, there may be surprise windfalls in budgets for maintenance activities due to decreased costs for “unplanned” maintenance. In these cases, how should we resolve capital budgeting when we have risk forecasts for costs, profits and budgets? One approach we proposed in this summary is to re-solve the optimization models based on assumed statistical distributions of given parameters. If these distributions were not available, a two-stage stochastic optimization approach can be used to provide priority lists to decision-makers to support better risk-informed decisions [4, 5]. In this summary, we will only focus on the first approach.

42 ENGINEERING↗
DOE OSTI2021

A moving morphable component‐based topology optimization approach considering transient structural dynamic responses

Abstract A novel approach is developed under the moving morphable component (MMC) framework to solve topology optimization problems considering transient structural dynamic responses, where the structure for optimization is constructed with a collection of structural components, and the structural layout can be described explicitly via only a small number of design variables characterizing the positions and geometries of the components. The transient dynamic response of the structure and corresponding sensitivities are computed via step‐by‐step numerical integration and mode reduction technique is also employed to enhance the computational efficiency. Compared with existing works, the numerical instabilities induced by localized vibration modes can be substantially alleviated and the computational effort for direct sensitivity analysis is significantly reduced in the proposed approach. Two and three‐dimensional numerical examples considering the cases of nonproportional damping mechanism and time‐varying mass are also provided to manifest the validity of the proposed approach.

Li, Jialin↗
DOE OSTI2023

Investigating Various Failure Models on Commercial Silicon Carbide

Structures and components made from ceramic materials are often brittle and can fail by the unstable growth of existing flaws such as voids and cracks. There have been several failure criteria developed for ceramics, in the past and they are broadly categorized based on their dependency on crack geometry. The present work implements eight failure criteria using an open-source software package – srlife, which predicts the lifetime or failure probability of concentrated solar power (CSP) structural components. The present work also checks the viability of building a ceramic CSP receiver, by analyzing the reliability predictions from srlife for a SiC ceramic. The reliability predictions for a biaxial loading problem indicated the Shetty Mixed-Mode criterion gives the most conservative predictions. Whereas, in case of the CSP receiver, the predictions show that the co-planar strain energy criterion gives the most conservative predictions as it is agnostic towards the type of stress, and therefore, is not recommended to be used designing ceramic receivers.

Chaugule, Pawan (ORCID:0000000275706572)↗
DOE OSTI2023

Efficient structure-factor modeling for crystals with multiple components

Diffraction intensities from a crystallographic experiment include contributions from the entire unit cell of the crystal: the macromolecule, the solvent around it and eventually other compounds. These contributions cannot typically be well described by an atomic model alone, i.e . using point scatterers. Indeed, entities such as disordered (bulk) solvent, semi-ordered solvent ( e.g. lipid belts in membrane proteins, ligands, ion channels) and disordered polymer loops require other types of modeling than a collection of individual atoms. This results in the model structure factors containing multiple contributions. Most macromolecular applications assume two-component structure factors: one component arising from the atomic model and the second one describing the bulk solvent. A more accurate and detailed modeling of the disordered regions of the crystal will naturally require more than two components in the structure factors, which presents algorithmic and computational challenges. Here an efficient solution of this problem is proposed. All algorithms described in this work have been implemented in the computational crystallography toolbox ( CCTBX ) and are also available within Phenix software. These algorithms are rather general and do not use any assumptions about molecule type or size nor about those of its components.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Assessment of Acoustic Sensor Application to Structural Health Monitoring of Reactor Components

The objectives of SHM of advanced fission reactors include the following: (1) Maintain safe, reliable, and efficient operation of structures, systems, and components in accordance with design intent; (3) Reduce cost; (4) Improve the comprehensive life management of structures, systems, and components; and (5) Extend the operational life of a power system through retirement for cause. Advanced reactor designs currently being considered are expected to operate at higher temperatures than light water-cooled reactors and to support missions beyond baseload electricity generation. Methods to monitor and detect for these mechanisms will require structural health monitoring (SHM) techniques, with ultrasonic methods an ideal candidate given their widespread use for NDE. This document summarized the state of technology for ultrasonic technologies, as part of an assessment of technology gaps and needed research. The great majority of sensor development to date addresses elevated temperatures and radiation tolerance, and more work is needed in both areas. Little data exists regarding corrosion effects of advanced coolants on sensor materials and couplants. Of high importance is the need for ARDs and regulatory bodies to engage and define what level of SHM is needed for autonomous or semi-autonomous control of reactors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Experimental Fabrication of Porous Additive Manufactured Material

Nuclear industries can benefit from materials that can perform well mechanically and thermally in high temperature and corrosion environments. Functionally graded materials (FGM) are materials manufactured with complex spatial, structural, and chemical compositions, creating components predesigned with tailored microstructural and mechanical properties. Porosity-graded FGMs are designed to introduce pores into a component’s structure as a mechanism to increase bulk or surface material performance, such as stress accommodation and negative thermal conductivity. Additive manufacturing (AM) techniques such as laser energy net shape (LENS) and wire arc additive manufacturing (WAAM), excel in high energy density, point-to-point metal deposition, and present in combination with other combinatorial approaches, exciting methods to manufacture porous FGM components. This project is also examining plasma jet printing as another means for method evaluations for smaller scale graded components. This study explores AM FGM process parameters and combinatorial fabrication methodologies for stainless steel components functionally graded in porosity levels. Preliminary characterization results are provided to attest the feasibility of the combinational fabrication techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Light Water Reactor Sustainability: Program Materials Research Pathway (FY22 Technical Program Plan)

The Materials Research (MR) Pathway within the Light Water Reactor Sustainability (LWRS) program is charged with performing R&D to develop the scientific basis for understanding and predicting the long-term environmental degradation behavior of materials in nuclear reactors. Furthermore, the mechanistic understanding of degradation phenomena in materials must be leveraged to develop mitigation and repair strategies and new material alternatives for existing components. This research will provide data and methods to assess the performance of systems, structures, and components essential to safe and sustained reactor operations. The R&D products developed from the LWRS program will be used by stakeholders—including utilities, industry groups, and regulators—to inform operational and regulatory requirements for materials in reactor systems, structures, and components subjected to long-term operation conditions, providing key inputs to regulators and industry. Therefore, the intent of this research is to provide options to reduce the operating costs, which may be in the form of offset maintenance costs due to better predictive models for component lifetimes, improved analyses of materials through nondestructive evaluation, reduced costs for repairs, or extended performance of plants through the selection of improved replacement materials. To provide the best options, industry experience and guidance are important because of their role in coordinated or collaborative research projects. The objectives of this report are to describe the motivation and organization of the MR Pathway within the LWRS program; provide details on the individual research tasks within the MR Pathway; describe the outcomes and deliverables of the MR Pathway, including recent technical highlights and progress; and describe the requirements for performing this critically important research.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Accelerating Large-Format Metal Additive Manufacturing: How Controls R&D is Driving Speed, Scale, and Efficiency

This article highlights work at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility to develop closed-loop, feedback control for laser-wire based Directed Energy Deposition, a form of metal Big Area Additive Manufacturing (m-BAAM), a process being developed in partnership with GKN Aerospace specifically for the production of Ti-6Al-4V pre-forms for aerospace components. A large-scale structural demonstrator component is presented as a case-study in which not just control, but the entire 3D printing workflow for m-BAAM is discussed in detail, including design principles for large-format metal AM, toolpath generation, parameter development, process control, and system operation, as well as post-print net-shape geometric analysis and finish machining. In terms of control, a multi-sensor approach has been utilized to measure both layer height and melt pool size, and multiple modes of closed-loop control have been developed to manipulate process parameters (laser power, print speed, deposition rate) to control these variables. Layer height control and melt pool size control have yielded excellent local (intralayer) and global (component-level) geometry control, and the impact of melt pool size control in particular on thermal gradients and material properties is the subject of continuing research. Further, these modes of control have allowed the process to advance to higher deposition rates (exceeding 7.5 lb/hr), larger parts (1-meter scale), shorter build times, and higher overall efficiency. The control modes are examined individually, highlighting their development, demonstration, and lessons learned, and it is shown how they operate concurrently to enable the printing of a large-scale, near net shape Ti-6Al-4V component.

Gibson, Brian↗
DOE OSTI2025

C3MechLite: An integrated component library of compact kinetic mechanisms for low-carbon, carbon neutral and zero-carbon fuels

Based on our latest detailed chemical reaction mechanism, C3MechV4.0, we have developed two reduced reaction mechanisms—C3MechLite and C3MechCore—targeting C 0 –C 3 chemical species including NH 3 . C3MechLite (61 species), contains a number of species comparable to GRI-Mech (53 species), that can accurately predict the combustion characteristics of hydrogen, carbon monoxide, ammonia, methane, natural gas, nitrogen oxides, and their mixtures for a wide range of conditions. C3MechCore (118 species) targets a more comprehensive range of C 0 –C 3 fuels, including ammonia, methanol, ethanol, and dimethyl ether. Both mechanisms demonstrate predictive accuracy comparable to C3MechV4.0 for the combustion characteristics of the target fuels. C3MechLite is designed with a component library structure, enabling further reduction in mechanism size depending on the fuel(s) of interest for 2D/3D numerical simulations. Various combinations of component libraries were validated, and the average prediction error remains within 1 % compared to C3MechLite. Furthermore, the mechanism was applied to 3D LES simulations of H 2 lifted flames and was confirmed to reproduce flame characteristics with high accuracy. C3MechLite and its component library structure enable high-fidelity and computationally efficient chemical kinetic mechanisms, paving the way for application in more complex combustion simulations.

Ammonia↗
DOE OSTI2025

Effects of Central Cut Width on the Dynamical Characteristics of Box Assembly Structure

An investigation into the Box Assembly with Removable Component (BARC) structure is conducted by utilizing computational simulations and experimental structural testing in order to determine the complex dynamical responses instigated by the central cut of the system. Because the dynamics of the BARC system is complex, this study focuses primarily on analyzing the behavior of the box assembly (BA) system. The investigation explores the dynamics of the BA system by varying the central cut widths, ranging from a cut as wide as 0.5” cut to a 0.25” cut system, as well as a 0.1” cut and a system with no cut at all. Experimental testing is performed on each system including a free vibration test using an impact hammer to excite and identify the dominant frequencies of each structure. This testing is followed by pseudo-random vibration tests and swept sinusoidal excitation tests to determine the nonlinear aspects of these systems, such as the possible existence of nonlinear softening, hardening, and/or damping. The results show that nonlinear softening and nonlinear damping are present in each system. The no-cut system demonstrated the highest peak frequencies throughout all the tests, being the most rigid structure. The 0.25” cut system was shown to have the highest peak frequencies among all the cut systems in both the finite elemenet analysis (FEA) and impact testing. This trend did not continue, though, in the random and harmonic testing, possibly due to the added stiffness of the test setup with the slip table and stinger. The results show the importance of accurately measuring the central cut width and how possible geometric uncertainties change the overall dynamical behaviors of complex systems, such as natural characteristics, nonlinear responses, coupling of modes, and oscillating amplitudes.

Padilla, Christopher (ORCID:000900033446732X)↗
DOE OSTI2025

Non-destructive structural characterization of graphite components using mechanical resonance and deep learning

As compared to conventional nuclear reactors, microreactors have the potential to significantly reduce construction timelines and capital costs, decreasing the barriers for advanced nuclear reactor technologies. However, the lower power output of these microreactors (typically < 20 MWe) creates challenging economics if operation and maintenance costs cannot be sufficiently reduced. The compact size of these designs presents an opportunity for comprehensive in-situ structural health monitoring to provide real-time feedback in order to reduce operational costs associated with maintenance and downtime. Many microreactor concepts use graphite for both in-core neutron moderation and as a structural material, which has typically required some form of periodic and laborious inspection. This report provides a description and assessment of recent work with graphite to couple acoustic-based experimental measurements and characterization with machine learning models to mature structural health monitoring capabilities and generate benefits for the nuclear microreactor industry. With resilient embedded sensors in development in other programs funded by the US Department of Energy’s Office of Nuclear Energy and elsewhere, the work described herein builds upon previously funded efforts to mature non-destructive testing technology that relates measured vibrational signatures to structural changes, using a combination of new experimental measurements and machine learning processing. Building on past successful demonstrations of predictive workflows to identify structural changes in a hexagonal stainless steel test article with excellent acoustic propagation, we first performed baseline characterization on graphite samples with canonical geometries to ensure compatibility and confidence in the applied techniques for a material with distinctly different mechanical properties. In contrast to efforts in previous years, we worked exclusively with unidirectional vibration data that is more comparable to those expected from the existing embedded sensor technologies which are suitable for deployment in a reactor setting. Established acoustic and modern machine-learning-based characterization approaches were applied to the resulting datasets from these simple geometries. Both approaches were found to be highly capable of detecting even small geometric irregularities amongst nominally identical samples. As such, we then moved to testing these approaches for detection of artificial local stress perturbations introduced into a more complex geometry: a hexagonal block with drilled holes. A main outcome of this work is that a generalizable ML workflow can be used to detect and predict the characteristics of small artificial anomalies in a graphite component with a relevant geometry. While this work was performed using surficial vibration data, we expect the approach to be flexible and viable for other monitoring scenarios, such as those with different arrangements or types of sensor arrays. As compared to previously funded efforts, an existing ML workflow based on neural networks was enhanced through the addition of recently developed Fourier neural operators. As applied to previously collected and new vibration datasets, prediction accuracies of anomaly characterizations were greatly improved with minimal added computational cost. As trained on small durations of vibration data (tens of seconds) collected over a realistic number of locations, the model was able to reliably determine the presence of a subtle stress anomaly and begin to provide location estimates. Such an approach is likely to be viable for more relevant reactor damage scenarios for graphite components, such as progressive crack growth or creep.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The influence of molecular design on structure–property relationships of a supramolecular polymer prodrug

Supramolecular self-assemblies of hydrophilic macromolecules functionalized with hydrophobic, structure-directing components have long been used for drug delivery. In these systems, loading of poorly soluble compounds is typically achieved through physical encapsulation during or after formation of the supramolecular assembly, resulting in low encapsulation efficiencies and limited control over release kinetics, which are predominately governed by diffusion and carrier degradation. To overcome these limitations, amphiphilic prodrugs that leverage a hydrophobic drug as both the therapeutic and structure-directing component can be used to create supramolecular materials with higher loading and controlled-release kinetics using biodegradable or enzymatically cleavable linkers. Here, we report the design, synthesis, and characterization of a library of supramolecular polymer prodrugs based on poly(ethylene glycol) (PEG) and the proregenerative drug 1,4-dihydrophenonthrolin-4-one-3-carboxylic acid (DPCA). Structure–property relationships were elucidated through experimental characterization of prodrug behavior in both the wet and dry states using scattering techniques and electron microscopy and corroborated by coarse-grained modeling. Molecular architecture and the hydrophobic-to-hydrophilic ratio of PEG–DPCA conjugates strongly influenced their physical state in water, ranging from fully soluble to supramolecular spherical assemblies and nanofibers. Molecular design and supramolecular structure, in turn, were shown to dramatically alter hydrolytic and enzymatic release and cellular transport of DPCA. In addition to potentially expanding therapeutic options for DPCA through control of supramolecular assemblies, the design principles elaborated here may inform the development of other supramolecular prodrugs based on hydrophobic small-molecule compounds.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Pulsed laser deposition and structural evolution of BaF 2 nanolayers in Eu-doped BaF 2 /Al 2 O 3 layered optical nanocomposite thin films

Here, we have developed a pulsed laser deposition (PLD) geometry for the growth of uniform BaF 2 nanoscale thin films, through control of the deposition conditions. Our goal is to use the BaF 2 layers with controllable structure as component layers in layered optical nanocomposites. The structure of the BaF 2 nanolayer evolves as a function of the layer thickness: BaF 2 grows via a layer-by-layer growth mode on Al 2 O 3 ; the layers are amorphous for a thickness < 3 nm, and then become nanocrystalline as the layer thickness increases. The BaF 2 nanocrystals have an FCC crystal structure with a weak < 111 > texture that becomes stronger for thicker films. We then demonstrate that our BaF2 films can be introduced into layered Al 2 O 3 /BaF 2 /EuO x nanocomposite films, which allows for control of the relative position of the Eu ions and the BaF 2 layer. Cross-section samples of the multilayered films show interfacial intermixing between the layers, which is related to implantation during the PLD process. This intermixing enables the incorporation of Eu ions into BaF 2 layers and form a thin Eu-doped BaF 2 nanolayer at the interface. The layered nanocomposite films show photoluminescence (PL) emission from Eu 3+ ions, and the PL intensity changes can be correlated with the crystallinity and crystal size changes in the BaF 2 layer. Our results provide guidance for achieving thin film nanocomposite materials with controllable structure and photoluminescence behavior for light emitting diodes, photovoltaics and other optical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Development of a Reconstruction Methodology Based on X-Ray Computed Tomography to Generate Realistic 3D Concrete Microstructures in MOSAIC

Despite being passive components, concrete structures represent a major capital investment in nuclear power plants. However, some concrete components are critical for the safety and long-term operation of the reactors: the concrete containment building protects the reactors from external aggression. The concrete biological shield (CBS) contains the radiation exiting the reactor to protect equipment and personnel. Depending on the design, the CBS also has a function for supporting the reactor’s systems. This function needs to be ensured in-service and during accident scenarios. After several decades of use, the CBS is exposed to high-energy irradiation over an extended operation time, exceeding the fluence level currently considered detrimental for the concrete’s structural properties. Such conditions occur at different times depending on the reactor’s operation and design. Nevertheless, from the perspective of subsequent license application, it is mandatory to assess the potential effects of prolonged irradiation on concrete. Unlike steel components, concrete structures are built with local constituents (cement, sand, and coarse aggregates) to avoid prohibitive transportation costs. Thus, concrete performance is determined by the tolerance or the susceptibility of its constituents against any aging mechanism. The tolerance against irradiation of the CBSs may vary greatly among the 56 nuclear power plants and 93 nuclear power reactors that form the current US light-water reactor fleet. Irradiation-induced degradation is mainly a result of amorphization-induced expansions of the silicated minerals present in the aggregates. The neutron irradiation–induced expansion varies from one rock-forming mineral to another: well framework–structured silicates (e.g., quartz and feldspars) exhibit higher swelling than chained (e.g., pyroxene) or isolated silicates (e.g., garnet). Silicates make up nearly 90% of the Earth’s crust. Other common minerals present in construction aggregates are carbonates found, for example, in limestone. Irradiated carbonates exhibit only very minor expansions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Verification of numerical models for seismic fluid-structure interaction analysis of internal components in liquid-filled advanced reactors

Earthquake shaking of a liquid-filled advanced reactor induces fluid-structure interaction (FSI) between the reactor vessel (tank), its internal components, and the contained liquid. Seismic design, qualification, and risk assessment of such reactors must consider fluid-structure responses, their geometries and support conditions, and three-directional seismic inputs, all of which require numerical simulations. Numerical models used for analysis of safety-related nuclear equipment must be verified and validated. Here, this paper verifies numerical models of submerged components using analytical solutions. Seismic FSI analysis of the numerical models is performed using the Arbitrary Lagrangian-Eulerian (ALE) and Incompressible Computational Fluid Dynamics (ICFD) solvers in LS-DYNA. Prior analytical solutions are reworked in this paper, and calculation errors are identified and corrected. The solutions address frequencies of two concentric cylindrical pipes filled with liquid: the inner pipe is a submerged component, and the outer pipe contains the liquid. A unitless frequency coefficient is defined and presented for pipes of different materials, filled with different liquids, and with a range of dimensions for application to advanced reactors. The numerical models are verified here by comparing the lateral frequencies of submerged components with those calculated using the corrected analytical solutions. Recommendations for verification of numerical models of internal components in advanced reactors for seismic FSI analysis are provided. Although the unitless frequency coefficients and verification procedures are developed for application to advanced nuclear reactors, they are broadly applicable to FSI analysis of submerged components in liquid-filled vessels such as storage tanks, boilers, and steam generators.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗