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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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All sources NASA NTRS DOE OSTI

DOE OSTI2022

American Made Challenges Battery Voucher Program Cooperative Research and Development Agreement (Cooperative Research and Development Final Report, CRADA Number CRD-21-17533)

Renewance is a Phase II winner of the U.S. Department of Energy Lithium-ion Battery Recycling Prize. The Prize is designed to incentivize American entrepreneurs to develop and demonstrate processes that, when scaled, have the potential to profitably capture 90% of all discarded or spent lithium-based batteries (LIB) in the Unites States for eventual recovery of key materials for re-introductions into the U.S. supply chain. The objective of this work is to enable a more efficient evaluation of battery sources for second life applications prior to ultimately being recycled, through evaluation of chemistry characteristics, projected battery lifetime, and application history. This work will develop the capability to identify groups of batteries that may be useful for second life and reduce the cost of end-of-life (EOL) LIB evaluation and repurposing. To meet the objective, NREL will use existing and new data to create a refined algorithm that could be used to evaluate batches of batteries for potential reuse based on manufacturing date and historical use characteristics. Based on current battery market prices and compiled literature data, a starting-point estimate of the market value of the batteries for reuse based on expected lifetime will be included in the algorithm. With the projected surge in LIB demand, battery second life is a new area ripe for development and investment from companies like Renewance. With so few large format batteries reaching EOL to date, this is a new market with a variety of areas for optimization and adding value. This work with Renewance is an example of how existing expertise in battery degradation at NREL can be used to reduce the cost of shifting a battery into a second life application. With these cost reductions, this work is also facilitating the development of a battery circular economy in the United States. A robust circular economy can maximize the utilization of critical metals demanded by battery technology such as nickel and cobalt while also reducing the costs of batteries in the marketplace for the many end-uses needed for the green energy transition. The supply of these metals is limited, and we face a supply chain shortage both domestically and globally unless we can ensure they are being used to their maximum potential. This research can improve the economics of a battery circular economy to make it a more likely path for EOL batteries with critical metals. CRADA benefit to DOE, Participant, and US Taxpayer: assists laboratory in achieving programmatic scope competencies, uses the laboratory's core competencies.

25 ENERGY STORAGE↗

DOE OSTI2022

Life cycle assessment of the wood pallet repair and remanufacturing sector in the United States

Wood pallets are ubiquitous products that can be recovered and reused to enhance their service life and environmental performance. Repair/remanufacturing has an important role in extending the service life of the wood pallet. To quantify environmental performances of wood pallet reuse, this study developed representative life cycle inventory data for pallet repair/remanufacturing in the United States based on comprehensive industry-wide production data for 2018. A gate-to-gate life cycle assessment covering raw material supply, raw material transportation and pallet repair/remanufacturing showed that repair/remanufacturing often had the highest impacts, including primary energy consumption at 5.09 MJ and global warming impact at 0.355 kg CO 2 eq per repaired/remanufactured pallet. Electricity consumed onsite followed by nail input and the fuel used by forklifts during the manufacturing drove much of the impacts on the environment. Finally, the results of this study provide valuable information on the repair/remanufacturing impacts, allowing quantification and evaluation of the recovery stage on the overall environmental performance of wood pallets.

09 BIOMASS FUELS↗

NASA NTRS2009

Economical Implementation of a Filter Engine in an FPGA

A logic design has been conceived for a field-programmable gate array (FPGA) that would implement a complex system of multiple digital state-space filters. The main innovative aspect of this design lies in providing for reuse of parts of the FPGA hardware to perform different parts of the filter computations at different times, in such a manner as to enable the timely performance of all required computations in the face of limitations on available FPGA hardware resources. The implementation of the digital state-space filter involves matrix vector multiplications, which, in the absence of the present innovation, would ordinarily necessitate some multiplexing of vector elements and/or routing of data flows along multiple paths. The design concept calls for implementing vector registers as shift registers to simplify operand access to multipliers and accumulators, obviating both multiplexing and routing of data along multiple paths. Each vector register would be reused for different parts of a calculation. Outputs would always be drawn from the same register, and inputs would always be loaded into the same register. A simple state machine would control each filter. The output of a given filter would be passed to the next filter, accompanied by a "valid" signal, which would start the state machine of the next filter. Multiple filter modules would share a multiplication/accumulation arithmetic unit. The filter computations would be timed by use of a clock having a frequency high enough, relative to the input and output data rate, to provide enough cycles for matrix and vector arithmetic operations. This design concept could prove beneficial in numerous applications in which digital filters are used and/or vectors are multiplied by coefficient matrices. Examples of such applications include general signal processing, filtering of signals in control systems, processing of geophysical measurements, and medical imaging. For these and other applications, it could be advantageous to combine compact FPGA digital filter implementations with other application-specific logic implementations on single integrated-circuit chips. An FPGA could readily be tailored to implement a variety of filters because the filter coefficients would be loaded into memory at startup.

Kowalski, James E.↗

NASA NTRSDate not supplied

Gimbal Bearing Friction in the SLS Core Stage Thrust Vector Control System

The Space Launch System (SLS) Core Stage Thrust Vector Control (TVC) system is comprised of eight mechanical feedback Shuttle heritage Type III TVC actuators that vector the four Shuttle heritage RS-25 engines about a Shuttle heritage gimbal block/bearing. The MSFC Controls community has long regarded gimbal friction to be a negligible effect on the overall control of gimbaled RS-25 engines. This is corroborated by Space Shuttle test and flight data that does not appear to show degraded effects, nor limit cycling at the end of the shuttle flight. For this reason, friction was not expected to be a driving factor of performance and control of the reused RS-25 engines aboard the SLS. However, after test data showed a large shift in frequency behavior and a highly damped step-response in the time series, there was further investigation into what could have caused this behavior. Heritage friction models used in previous gimbal and ball bearings were evaluated such as Coulomb, Dahl and LuGre, but the single degree of freedom friction models alone were not enough to explain the behavior and shifts seen in the test data. This paper presents the additional findings and modeling efforts regarding friction on the RS-25 engines. Using the Two Actuator Operational Simulation (TAOS), the difference from modeling separate friction degrees of freedom to coupled degrees of freedom was investigated to deduce the effects of one axis’s movement on the other. Next, due to the vibration environment, a modified LuGre model has been proposed that adds an additional term to decrease the friction coefficient at low engine velocity amplitudes. Lastly, the addition of the stiffness in each half of the gimbal bearing has increased modeling fidelity by also adding the effect on the gimbal bearing bending in compliance to both the friction torque on the surface of the gimbal bearing and the actuator force that is forcing the engine in a specified direction. Through these effects, the time and frequency domain behavior seen in test can be characterized accurately.

Friction↗

NASA NTRSDate not supplied

Gimbal Bearing Friction in the SLS Core Stage Thrust Vector Control System

Friction↗

DOE OSTI2024

Identifying genomic data use with the Data Citation Explorer

Increases in sequencing capacity, combined with rapid accumulation of publications and associated data resources, have increased the complexity of maintaining associations between literature and genomic data. As the volume of literature and data have exceeded the capacity of manual curation, automated approaches to maintaining and confirming associations among these resources have become necessary. Here we present the Data Citation Explorer (DCE), which discovers literature incorporating genomic data that was not formally cited. This service provides advantages over manual curation methods including consistent resource coverage, metadata enrichment, documentation of new use cases, and identification of conflicting metadata. The service reduces labor costs associated with manual review, improves the quality of genome metadata maintained by the U.S. Department of Energy Joint Genome Institute (JGI), and increases the number of known publications that incorporate its data products. The DCE facilitates an understanding of JGI impact, improves credit attribution for data generators, and can encourage data sharing by allowing scientists to see how reuse amplifies the impact of their original studies.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Electricity use in big area additive manufacturing of fiber-reinforced polymer composites

In recent years, additive manufacturing (AM), especially large-format additive manufacturing (LFAM), has gained momentum in the manufacturing industry. While LFAM offers benefits over conventional manufacturing processes, such as minimizing material waste and providing vast geometric freedom, assessing its sustainability remains challenging due to limited data, particularly on energy consumption. Most existing data pertain to small-scale or desktop AM and are not directly applicable to LFAM. In this study, we conducted real-time measurements of electricity usage for a type of LFAM known as big area additive manufacturing (BAAM), which typically uses fiber-reinforced polymer pellets as feedstock. We collected electricity usage data from fifteen printing jobs over two months in an industrial production setting. These data fill the existing gap and can be reused to enhance the community’s understanding of LFAM electricity usage, support further research, and promote sustainable development in advanced manufacturing technologies.

ecology↗

DOE OSTI2024

Data Citation Explorer (DCE) v1.0

Increases in sequencing capacity, combined with rapid accumulation of publications and associated data resources, have increased the complexity of maintaining associations between literature and genomic data. As the volume of literature and data have exceeded the capacity of manual curation, automated approaches to maintaining and confirming associations among these resources have become necessary. Here we present the Data Citation Explorer (DCE), which discovers literature incorporating genomic data whether or not provenance was clearly indicated. This service provides advantages over manual curation methods including consistent resource coverage, metadata enrichment, documentation of new use cases, and identification of conflicting metadata. The service reduces labor costs associated with manual review, improves the quality of genome metadata maintained by the U.S. Department of Energy Joint Genome Institute (JGI), and increases the number of known publications that incorporate its data products. The DCE facilitates an understanding of JGI impact, improves credit attribution for data generators, and can encourage data sharing by allowing scientists to see how reuse amplifies the impact of their original studies.

Parker, Charles↗

NASA NTRS1986

An empirical study of software design practices

Software engineers have developed a large body of software design theory and folklore, much of which was never validated. The results of an empirical study of software design practices in one specific environment are presented. The practices examined affect module size, module strength, data coupling, descendant span, unreferenced variables, and software reuse. Measures characteristic of these practices were extracted from 887 FORTRAN modules developed for five flight dynamics software projects monitored by the Software Engineering Laboratory (SEL). The relationship of these measures to cost and fault rate was analyzed using a contingency table procedure. The results show that some recommended design practices, despite their intuitive appeal, are ineffective in this environment, whereas others are very effective.

Card, David N.↗

NASA NTRS1994

SCL: An off-the-shelf system for spacecraft control

In this age of shrinking military, civil, and commercial space budgets, an off-the-shelf solution is needed to provide a multimission approach to spacecraft control. A standard operational interface which can be applied to multiple spacecraft allows a common approach to ground and space operations. A trend for many space programs has been to reduce operational staff by applying autonomy to the spacecraft and to the ground stations. The Spacecraft Command Language (SCL) system developed by Interface and Control Systems, Inc. (ICS) provides an off-the-shelf solution for spacecraft operations. The SCL system is designed to provide a hyper-scripting interface which remains standard from program to program. The spacecraft and ground station hardware specifics are isolated to provide the maximum amount of portability from system to system. Uplink and downlink interfaces are also isolated to allow the system to perform independent of the communications protocols chosen. The SCL system can be used for both the ground stations and the spacecraft, or as a value added package for existing ground station environments. The SCL system provides an expanded stored commanding capability as well as a rule-based expert system on-board. The expert system allows reactive control on-board the spacecraft for functions such as electrical power systems (EPS), thermal control, etc. which have traditionally been performed on the ground. The SCL rule and scripting capability share a common syntax allowing control of scripts from rules and rules from scripts. Rather than telemeter over sampled data to the ground, the SCL system maintains a database on-board which is available for interrogation by the scripts and rules. The SCL knowledge base is constructed on the ground and uploaded to the spacecraft. The SCL system follows an open-systems approach allowing other tasks to communicate with SCL on the ground and in space. The SCL system was used on the Clementine program (launched January 25, 1994) and is required to have bidirectional communications with the guidance, navigation, and control (GNC) algorithms which were written as another task. Sequencing of the spacecraft maneuvers are handled by SCL, but the low-level thruster pulse commands are handled by the GNC software. Attitude information is reported back as telemetry, allowing the SCL expert system to inference on the changing data. The Clementine SCL flight software was largely reused from another Naval Center for Space Technology (NCST) satellite program. This paper details the SCL architecture and how an off-the-shelf solution makes sense for multimission spacecraft programs. The Clementine mission will be used as a case study in the application of the SCL to a 'fast track' program. The benefits of such a system in a 'better, cheaper, faster' climate will be discussed.

Buckley, Brian↗

NASA NTRS1994

A Knowledge-Based Representation Scheme for Environmental Science Models

One of the primary methods available for studying environmental phenomena is the construction and analysis of computational models. We have been studying how artificial intelligence techniques can be applied to assist in the development and use of environmental science models within the context of NASA-sponsored activities. We have identified several high-utility areas as potential targets for research and development: model development; data visualization, analysis, and interpretation; model publishing and reuse, training and education; and framing, posing, and answering questions. Central to progress on any of the above areas is a representation for environmental models that contains a great deal more information than is present in a traditional software implementation. In particular, a traditional software implementation is devoid of any semantic information that connects the code with the environmental context that forms the background for the modeling activity. Before we can build AI systems to assist in model development and usage, we must develop a representation for environmental models that adequately describes a model's semantics and explicitly represents the relationship between the code and the modeling task at hand. We have developed one such representation in conjunction with our work on the SIGMA (Scientists' Intelligent Graphical Modeling Assistant) environment. The key feature of the representation is that it provides a semantic grounding for the symbols in a set of modeling equations by linking those symbols to an explicit representation of the underlying environmental scenario.

Keller, Richard M.↗

NASA NTRS1989

Study of spread spectrum multiple access systems for satellite communications with overlay on current services

The feasibility of using spread spectrum techniques to provide a low-cost multiple access system for a very large number of low data terminals was investigated. Two applications of spread spectrum technology to very small aperture terminal (VSAT) satellite communication networks are presented. Two spread spectrum multiple access systems which use a form of noncoherent M-ary FSK (MFSK) as the primary modulation are described and the throughput analyzed. The analysis considers such factors as satellite power constraints and adjacent satellite interference. Also considered is the effect of on-board processing on the multiple access efficiency and the feasibility of overlaying low data rate spread spectrum signals on existing satellite traffic as a form of frequency reuse is investigated. The use of chirp is examined for spread spectrum communications. In a chirp communication system, each data bit is converted into one or more up or down sweeps of frequency, which spread the RF energy across a broad range of frequencies. Several different forms of chirp communication systems are considered, and a multiple-chirp coded system is proposed for overlay service. The mutual interference problem is examined in detail and a performance analysis undertaken for the case of a chirp data channel overlaid on a video channel.

Ha, Tri T.↗

DOE OSTI2020

US Potable Water Reuse System Costs

This submission contains a set of U.S.-specific potable reuse capital and operations and maintenance (O&M) cost data ($2020) found in published presentations and reports from engineering consulting firms, utility and water agency press releases or websites, and literature. For any unbuilt facilities, the reported costs found in technical documents are mostly engineer estimates and may be subject to change as construction proceeds. This data set contains a mix of both facility specific and total capital costs, which include conveyance infrastructure. Note that this dataset does not include detailed cost breakdowns for each of the facilities. This submission also contains the sources used to build this dataset in pdf format.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

A semantics-driven framework to enable demand flexibility control applications in real buildings

Decarbonising and digitalising the energy sector requires scalable and interoperable Demand Flexibility (DF) applications. Semantic models are promising technologies for achieving these goals, but existing studies focused on DF applications exhibit limitations. These include dependence on bespoke ontologies, lack of computational methods to generate semantic models, ineffective temporal data management and absence of platforms that use these models to easily develop, configure and deploy controls in real buildings. This paper introduces a semantics-driven framework to enable DF control applications in real buildings. The framework supports the generation of semantic models that adhere to Brick and SAREF while using metadata from Building Information Models (BIM) and Building Automation Systems (BAS). The work also introduces a web platform that leverages these models and an actor and microservices architecture to streamline the development, configuration and deployment of DF controls. The paper demonstrates the framework through a case study, illustrating its ability to integrate diverse data sources, execute DF actuation in a real building, and promote modularity for easy reuse, extension, and customisation of applications. The paper also discusses the alignment between Brick and SAREF, the value of leveraging BIM data sources, and the framework's benefits over existing approaches, demonstrating a 75% reduction in effort for developing, configuring, and deploying building controls.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

SQUARE: Strategic Quantum Ancilla Reuse for Modular Quantum Programs via Cost-Effective Uncomputation

Compiling high-level quantum programs to machines that are size constrained (i.e. limited number of quantum bits) and time constrained (i.e. limited number of quantum operations) is challenging. In this paper, we present SQUARE (Strategic QUantum Ancilla REuse), a compilation infrastructure that tackles allocation and reclamation of scratch qubits (called ancilla) in modular quantum programs. At its core, SQUARE strategically performs uncomputation to create opportunities for qubit reuse. Current Noisy Intermediate-Scale Quantum (NISQ) computers and forward-looking Fault-Tolerant (FT) quantum computers have fundamentally different constraints such as data locality, instruction parallelism, and communication overhead. Our heuristic-based ancilla-reuse algorithm balances these considerations and fits computations into resource-constrained NISQ or FT quantum machines, throttling parallelism when necessary. To precisely capture the workload of a program, we propose an improved metric, the "active quantum volume," and use this metric to evaluate the effectiveness of our algorithm. Furthermore, our results show that SQUARE improves the average success rate of NISQ applications by 1.47X. Surprisingly, the additional gates for uncomputation create ancilla with better locality, and result in substantially fewer swap gates and less gate noise overall. SQUARE also achieves an average reduction of 1.5X (and up to 9.6X) in active quantum volume for FT machines.

compiler optimization↗

DOE OSTI2022

Agent-Based Modeling for the Circular Economy: Lessons Learned From Three Case Studies

The circular economy (CE) aims at decoupling human activities from resource use, creating wealth in the process. Recently, many scholars have questioned the link between increased circularity and sustainability, resulting in many methodological approaches being developed for that purpose. This presentation summarizes the insights gained from the application of agent-based modeling (ABM) to study the techno-economic and social conditions promoting circularity and sustainability of three technologies: photovoltaic (PV) modules, hard disk drives (HDDs), and wind blades. Four main categories of agents are defined in the ABM: asset owners, service providers (e.g., refurbishers), recyclers, and manufacturers. Two main CE strategies are represented: lifetime extension (through repair or reuse) and recycling. The developed models start by projecting installed capacities and end-of-life (EOL) quantities. Then the theory of planned behavior - a social psychology model explaining behavior adoption based on attitude, peer influence, and costs - is used to model the asset owners' EOL decision (i.e., landfill, recycle or extend the lifetime of the asset). Then, the quantities of assets flowing to the recycler and service provider agents and quantities of materials flowing to manufacturers are computed. Recyclers' economies of scale are dynamically modeled, and the value generated by the CE strategies for the recyclers, service providers, and manufacturers is computed within the model. When data are available, avoided greenhouse gas emissions resulting from the CE strategies adoption are calculated exogenously from the ABM simulations. Results show that with improved used PV modules warranties, the reuse CE strategy adoption increases from 1% to 23% between 2020 and 2050. Similarly, improved standards could enhance HDDs end-users trust in data-wiping - a prerequisite to reuse - leading to a 3-fold increase in the reuse rate and avoid about 5 million tons of CO2 eq by 2050. Regarding wind blades, 5-15 years lifetime extension could reduce EOL blade quantities by 13%. High costs and logistic issues prevent blades from being recycled in greater quantities. One insight from the case studies is the necessity to have mature secondary markets for reuse to be a viable option. Interestingly, PV reuse is limited by the willingness of PV owners to purchase used modules (on the demand side), while HDDs reuse is constrained by the lack of trust toward data-wiping (limiting the supply of used HDDs). The six limits of the CE concepts presented by Korhonen et al. (2018) are finally used to interpret the results. The HDD case study is an exemplary lock-in, where the first accepted practice (shredding) retains most of the market. The PV results illustrate the technical limitation to reuse, as the growing demand cannot be supplied entirely with used PV modules. The wind case study shows the relevance of clearly defining physical flows - what type of waste should wind blades be considered, how should they be transported and landfilled? - a crucial consideration that also applies to PV modules. Finally, the three case studies highlight the relevance of studying a technology's technical, economic, and market material efficiency potentials altogether and the potential benefit of coupling ABM to life cycle assessment.

agent-based modeling↗

DOE OSTI2024

Models, data, and scripts associated with “Prediction of Distributed River Sediment Respiration Rates using Community-Generated Data and Machine Learning”

This data package is associated with the publication “Prediction of Distributed River Sediment Respiration Rates using Community-Generated Data and Machine Learning’’ submitted to the Journal of Geophysical Research: Machine Learning and Computation (Scheibe et al. 2024). River sediment respiration observations are expensive and labor intensive to obtain and there is no physical model for predicting this quantity. The Worldwide Hydrobiogeochemisty Observation Network for Dynamic River Systems (WHONDRS) observational data set (Goldman et al.; 2020) is used to train machine learning (ML) models to predict respiration rates at unsampled sites. This repository archives training data, ML models, predictions, and model evaluation results for the purposes of reproducibility of the results in the associated manuscript and community reuse of the ML models trained in this project. One of the key challenges in this work was to find an optimum configuration for machine learning models to work with this feature-rich (i.e. 100+ possible input variables) data set. Here, we used a two-tiered approach to managing the analysis of this complex data set: 1) a stacked ensemble of ML models that can automatically optimize hyperparameters to accelerate the process of model selection and tuning and 2) feature permutation importance to iteratively select the most important features (i.e. inputs) to the ML models. The major elements of this ML workflow are modular, portable, open, and cloud-based, thus making this implementation a potential template for other applications. This data package is associated with the GitHub repository found at Please see the file level metadata (flmd; “sl-archive-whondrs_flmd.csv”) for a list of all files contained in this data package and descriptions for each. Please see the data dictionary (dd; “sl-archive-whondrs_dd.csv”) for a list of all column headers contained within comma separated value (csv) files in this data package and descriptions for each. The GitHub repository is organized into five top-level directories: (1) “input_data” holds the training data for the ML models; (2) “ml_models” holds machine learning models trained on the data in “input_data”; (3) “scripts” contains data preprocessing and postprocessing scripts and intermediate results specific to this data set that bookend the ML workflow; (4) “examples” contains the visualization of the results in this repository including plotting scripts for the manuscript (e.g., model evaluation, FPI results) and scripts for running predictions with the ML models (i.e., reusing the trained ML models); (5) “output_data” holds the overall results of the ML model on that branch. Each trained ML model resides on its own branch in the repository; this means that inputs and outputs can be different branch-to-branch. Furthermore, depending on the number of features used to train the ML models, the preprocessing and postprocessing scripts, and their intermediate results, can also be different branch-to-branch. The “main-*” branches are meant to be starting points (i.e. trunks) for each model branch (i.e. sprouts). Please see the Branch Navigation section in the top-level README.md in the GitHub repository for more details. There is also one hidden directory “.github/workflows”. This hidden directory contains information for how to run the ML workflow as an end-to-end automated GitHub Action but it is not needed for reusing the ML models archived here. Please the top-level README.md in the GitHub repository for more details on the automation.

13C↗

NASA NTRS2012

NASA InterCenter Collaboration Increases ROI

Funding for National Aeronautics and Space Administration (NASA) space mission operations is tighter than ever in the current environment of federal government deficit reductions. Conventional wisdom would expect this environment to drive increasing competition between NASA centers for the limited available funds. However, recent inter-center activities at the Huntsville Operations Support Center (HOSC) at NASA's Marshall Space Flight Center emphasize collaboration rather than competition and demonstrate the value of partnerships to increase the return on shrinking investments. These efforts cover a variety of activities and potential returns. To facilitate sharing data from test and verification through operations without levying requirements on data format or software tools, the HOSC is working with multiple centers on an evolutionary path toward a distributed data architecture and archive. The approach reduces the required investment by allowing the partners to reuse their existing formats and tools, while facilitating gone ]stop h user visibility into and controlled access to the full complement of data regardless of user or data location. The HOSC is also working on two activities to promote sharing operations implementations and leveraging the experts and expertise across multiple NASA sites. In one, the use of Consultative Committee for Space Data Systems (CCSDS) standards for the message abstraction layer provides an interoperability layer on top of existing ground data system communication architectures. This allows missions to select the most appropriate solutions for their requirements with a minimal investment in rehosting the components in a coherent operational environment. The other emphasizes shared tools and increased remote access to minimize travel for tests and critical activities and reduce the floor space required for a dedicated operations center. This paper summarizes these and other inter-center collaboration activities at the HOSC and the benefits that each can bring, not just to the participants, but to the broader operations community.

Lankford, Kimberly↗