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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Potential Formation Damage: An Integrated Reservoir Characterization Study of the Naturally Fractured Carbonate Middle Duperow Formation at the Kevin Dome, Montana

In this study, we integrate geologic and engineering data of a naturally fractured carbonate reservoir at the Kevin Dome, Montana. Well test data are correlated with core description, geochemical and lithology study to determine the flow behavior and communication within the injection test interval and to the surrounding area. Based on a dual-continuum geologic model, numerical brine injection simulations are carried out to validate the interpretation results from our well test analytical models and forecast the probability of CO 2 injection success using current reservoir properties. As a result, our well test analytical models as well as lithology/core description suggest that fluid flow may be mainly restricted to the injection interval and the assumption of radial (horizontal) flow may be appropriate. The well test models also indicate that there is potentially formation damage with a positive skin factor although prior to brine injection well tests, well stimulation through acid treatment was performed. Our numerical simulation results appear to confirm this formation damage by showing additional pressure buildup in the injection data during later test periods. To explain this, acid may have dissolved dolomite then dolomite or calcite may have been formed again further into the matrix/fracture system. Another possible explanation is mechanical clogging of the fractures due to acid dissolving dolomite and dislodging fine grains. Our work also predicts that if no additional well stimulation is performed, the project will have a lower probability of successfully injecting 1 million tons of CO 2 into the Middle Duperow formation over 4 years.

42 ENGINEERING↗
DOE OSTI2024

IDAES-PSE 2.5.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.5.0 Release Highlights Upcoming Changes IDAES will be switching to the new Pyomo solver interface in the next release. Whilst this will hopefully be a smooth transition for most users, there are a few important changes to be aware of. The new solver interface uses a different version of the IPOPT writer (“ipopt_v2”) and thus any custom configuration options you might have set for IPOPT will not carry over and will need to be reset. By default, the new Pyomo linear presolver will be activated with ipopt_v2. Whilst are working to identify any bugs in the presolver, it is possible that some edge cases will remain. IDAES will begin deploying a new set of scaling tools and APIs over the next few releases that make use of the new solver writers. The old scaling tools and APIs will remain for backward compatibility but will begin to be deprecated. New Models, Tools and Features New diagnostics check for near-parallel variables and constraints. New diagnostics tools for identifying causes of infeasibility in models. New example for creating a custom model of a liquid-liquid extractor unit operation. Bug Fixes Fixed bug in Gibbs reactor that caused it to appear to have additional spurious degrees of freedom. Fixed bug in the Modular Property Framework that would cause errors when trying to use phase-based material balances with phase equilibria. Fixed bug in Modular Properties Framework that caused errors when initializing models with non-vapor-liquid phase equilibria. Testing and Robustness Deployed the IDAES Diagnostics Toolbox to confirm that there are no structural or numerical issues in the core model libraries. Additional robustness tests for core model, and some associated improvements in the converge tester class. Fixed a number of issues that were causing unexpected warnings to be emitted during testing. Deprecations and Removals Removed examples for RIPE tool which has not been supported for a number of releases.

AS↗
DOE OSTI2015

High Performance Cold Climate Heat Pump (CCHP) – Final Report

In the U. S., there are approximately 2.6 million dwellings that use electricity for heating in very cold and cold regions with an annual energy consumption of 0.16 quads. A high performance cold climate heat pump (CCHP) would result in significant savings over current technologies (> 70% compared to strip heating). It can result in an annual primary energy savings of 0.1 Quads when fully deployed, which is equivalent to 5.9 million tons of annual CO2 emissions reduction. The outcome of this project is the development of a split system, cold climate heat pump (CCHP) providing 36,000 Btu/hr (10.6 kW) heating capacity with a COP > 4.0 (at the 47°F (8.3°C) AHRI rating condition) and maximum efficiency degradation of 50% and capacity loss of 25% at -13°F (-25°C) ambient conditions. Between 2012 and 2015, Oak Ridge National Laboratory (ORNL) and Emerson Climate Technologies engaged in a Cooperative Research and Development Agreement (CRADA) to develop a high efficiency, cold climate heat pump for the US residential market. We went through an exhaustive technologies survey to select energy efficient and cost-effective components. We conducted in-depth engineering design and building energy modeling, based on the ORNL Heat Pump Design Model (HPDM) and EnergyPlus, by which we made the final choices.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Simulating interactions of detonation, ionization chemistry, and magnetohydrodynamics

Detonation engines have the potential to remove NOx emissions from combustion based power generation by using high-temperature oxyfuel combustion. A magnetohydrodynamic (MHD) generator can directly extract power from ionized gases behind the detonation front (via the Lorentz force). This eliminates fragile moving components found in gas turbine engines unable to withstand high temperatures. Modeling detonations coupled with MHD requires the simultaneous consideration of interactions between compressible flow, chemical reactions, and an electro-magnetic field. This is achieved by coupling a Riemann solver, implicit ordinary differential equation integrators, and a Galerkin finite-element solver, which respectively solve the Euler, stiff chemical kinetics, and decoupled Maxwell equations. Each solver is separately verified and validated, and the coupled system is validated with literature results. Simulations of hydrogen and methane oxyfuel combustion are performed over a range of parameters to determine potential power extraction and emissions. In addition, seed particles are typically necessary to increase a fluid’s electrical conductivity through ionization. Therefore, impact of seed composition and quantity is also assessed. These results provide insight into the complex parasitic interactions between detonation, ionization, and MHD effects.

Zaiger, Matthew↗
DOE OSTI2018

Modeling the Long-Term Behavior of Cementitious Barriers - 18188

Cementitious materials are commonly included as backfill/barrier materials in geological repositories for radioactive waste. An understanding of the long-term behavior of cement-based barriers is therefore required to provide confidence in their safety functions within an environmental safety case. Geochemical modelling has been undertaken on several different radioactive waste repository concepts (and their natural/industrial analogues), to explore the nature of cement degradation over timescales relevant to postclosure safety (many tens of thousands of years to c. 1 Ma). In radionuclide transport calculations undertaken as part of performance assessments, it is typically considered that the properties of cementitious engineered barrier materials change as they degrade, potentially resulting in an increase in porosity hydraulic conductivity, and effective diffusion coefficients. However, reactive transport modelling (supported by some analogue data) suggests that, in some repository systems, a degree of clogging of the cement pore space could occur and that some advective flow paths (cracks in the barriers, fractures in the host rock) could become (to some extent) infilled by cement and rock alteration products. This could result in a reduction in water flow and contaminant transport in the vicinity of the cement-rock interface, but some uncertainties remain (especially process couplings and the nature of water flow in complex fracture networks that are becoming clogged). In addition, the armoring of fracture surfaces could result in decreased potential for diffusion of solutes into the rock matrix. It is envisaged that ongoing work will continue to improve reactive-transport model capabilities, such that the implications cement degradation has for contaminant transport can be predicted with greater confidence. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Analyzing count data with measurement error

In this article, we analyze observed count data such as the number of defects in a steel product where the observed counts are the true counts measured with errors. We account for the measurement error by using a measurement error model based on a latent lognormal (LLN) distribution. We consider making inference about a single population (e.g., from samples of a production lot) and a regression model (e.g., from runs of a designed experiment), where the measurement system properties are known, that is, the parameters of the LLN distribution are known. Then, we consider simultaneous inference for the single population and regression model as well as the measurement system. We demonstrate the proposed methodology with both simulated and real observed counts.

42 ENGINEERING↗
DOE OSTI2015

Performance Evaluation of Advanced Retrofit Roof Technologies Using Field-Test Data -- Phase Three Final Report, Volume 2

This article presents some miscellaneous data from two low-slope and two steep-slope experimental roofs. The low-slope roofs were designed to compare the performance of various roof coatings exposed to natural weatherization. The steep-slope roofs contained different combinations of phase change material, rigid insulation, low emittance surface and above-sheathing ventilation, with standing-seam metal panels on top. The steep-slope roofs were constructed on a series of adjacent attics separated at the gables using thick foam insulation. This article describes phase three (3) of a study that began in 2009 to evaluate the energy benefits of a sustainable re-roofing technology utilizing standing-seam metal roofing panels combined with energy efficient features like above-sheathing-ventilation (ASV), phase change material (PCM) and rigid insulation board. The data from phases 1 and 2 have been previously published and reported [Kosny et al., 2011; Biswas et al., 2011; Biswas and Childs, 2012; Kosny et al., 2012]. Based on previous data analyses and discussions within the research group, additional test roofs were installed in May 2012, to test new configurations and further investigate different components of the dynamic insulation systems. Some experimental data from phase 3 testing from May 2012 to December 2013 and some EnergyPlus modeling results have been reported in volumes 1 and 3, respectively, of the final report [Biswas et al., 2014; Biswas and Bhandari, 2014].

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Large Scale Metal Additive Manufacturing with Wolf Robotics

Large Scale Metal Additive Manufacturing (LSMAM) is a new additive manufacturing (AM) technology based on the metal arc welding. A continuously fed metal wire is melted by an electric arc that forms between the wire and the substrate, and deposited in the form of a bead of molten metal along the predetermined path. Objects are manufactured one layer at a time starting from the base plate. The final properties of the manufactured object are dependent on its geometry and the metal deposition path, in addition to depending on the basic welding process parameters. The focus of the first phase of this two phase program was the installation, initial operation and development of processing parameters to demonstrate the ability to manufacture metal large scale parts. If successful, the second phase will focus on the development, and validation, of process models for the system.

42 ENGINEERING↗
DOE OSTI2018

Strategy for Safety-Related Digital I&C Qualification

Digital I&C qualification continues to be a major impediment to addressing the reliability and obsolescence issues of the legacy analog I&C systems of the operating LWR fleet. In particular, the issue of digital common cause failure (CCF) has been difficult to address and has been the reason that some nuclear plant licensees have deferred upgrades of these critical plant systems and have rather opted to maintain them with considerable engineering and maintenance efforts. This is getting more and more difficult in the face of declining analog technology suppliers and dwindling supplies of spare parts and support for many critical components. To remain a viable energy source for the nation, the nuclear fleet must reduce its operating costs to a competitive level. Digital technology is the foremost means of implementing performance improvements and cost reductions for this purpose. This has been demonstrated over and over again in other industry sectors, as well as in conventional generation facilities. However, due to the special nature of nuclear energy, these digital I&C qualification barriers remain and must be resolved in order to modernize these plants and transform the business model to one that is competitive. The purpose of this report is to present an assessment of digital I&C qualification issues and address gaps in qualification methods and processes that would potentially benefit from Department of Energy (DOE)-sponsored research and development. Two new qualification methods are described that are recommended for further Department of Energy-sponsored research and development. They are 1) Testability – the exhaustive (100%) testing of certain digital devices addressing all combinations of inputs and internal states, and 2) Elimination of CCF triggers – ensuring that any latent digital defects are not concurrently triggered in redundant and back-up safety systems. In addition this report presents a strategy for full nuclear plant modernization based on four interrelated elements that together address the remaining barriers to prudent implementation. These four elements are 1) End-State Architecture, 2) Cost-Benefit Analysis, 3) Regulatory Approval, and 4) Implementation Sequence Plan.

42 ENGINEERING↗
DOE OSTI2021

Predicting Deformation of Parts from HP Printers due to Sintering with Modeling and Simulation (CRADA NFE-18-07363)

This work proposes to leverage Oak Ridge National Laboratory’s (ORNL) sintering simulation software developed at the Manufacturing Demonstration Facility to 1) investigate the deformation of sintered parts and 2) to develop fast surrogate-based optimization methods for HP Inc. This includes the development of ORNL’s software on HP systems, integration and testing with HP part geometries and material properties, the development of surrogate models based on the results of the simulation, and modifications to the software based on feedback from HP. The expected impacts of this work are a drastic reduction in print costs, an increase in printer throughput, and the identification of novel, possibly exotic materials for 3D printing. This work will also decrease the time to market for HP’s print technology by decreasing the amount of resources and type dedicated to physical testing.

42 ENGINEERING↗
DOE OSTI2023

Performance Evaluation of Heterogeneous GPU Programming Frameworks for Hemodynamic Simulations

Preparing for the deployment of large scientific and engineering codes on upcoming exascale systems with GPU-dense nodes is made challenging by the unprecedented diversity of device architectures and heterogeneous programming models. In this work, we evaluate the process of porting a massively parallel, fluid dynamics code written in CUDA to SYCL, HIP, and Kokkos with a range of backends, using a combination of automated tools and manual tuning. We use a proxy application along with a custom performance model to inform the results and identify additional optimization strategies. At scale performance of the programming model implementations are evaluated on pre-production GPU node architectures for Frontier and Aurora, as well as on current NVIDIA device-based systems Summit and Polaris. Real-world workloads representing 3D blood flow calculations in complex vasculature are assessed. Our analysis highlights critical trade-offs between code performance, portability, and development time.

Martin, Aristotle↗
DOE OSTI2024

Hydrogen Infrastructure Analysis for the Port Applications [Slides]

The International Maritime Organization has committed to 50% reduction in GHG emissions by 2050 worldwide as of 2023. This analysis includes performing an inventory and modeling efforts to understand the energy, equipment and cost requirements to support decarbonization of cargo handling and shore power at U.S. Ports, along with assessment of zero- and near- zero emission fuel supplies at or near U.S. ports focused upon Hydrogen technologies. Initial market assessment for ocean going vessels for harbor support and ocean-going vessels is explored. An energy analysis is performed on the port system using a holistic approach and considering the port as an entire ecosystem that functions as a transportation and energy node. Presently, a comprehensive view is lacking for future analysis efforts, this analysis seeks to address this gap in data by evaluating four representative port types and the potential for utilizing hydrogen for the maritime industry. Every port is different, but broadly they could be bracketed into reference cases with scaling factors for the relative size of the port operations. These reference ports are for future use, potentially as baselines for analysis and development of demonstration programs. An equipment inventory for each reference port type (container, bulk, breakbulk, and inland waterway) is presented. A comparative analysis of fuel cell electric and battery electric equipment is conducted based on the following criteria: technology readiness level, refueling/charging time, operational range, energy consumption, and fuel cost savings compared to baseline internal combustion engine equipment. The tradeoffs and synergies between two alternative powertrains is highlighted. Based on energy and infrastructure analysis, average and high equipment utilization profiles across different port types is identified and quantified baseline fuel and electricity demand for various decarbonization scenarios. Based on the portfolio of equipment converted to fuel cell electric, the estimates of initial capital investment are provided for hydrogen refueling stations across ports. An energy demand model is developed that predicts well the all-electric cargo handling equipment annual energy consumption for ports with annual tonnage under 2 million twenty-foot equivalent units (TEUs). The model is a good rubric to follow for further energy demand models that can create a scalable solution to understand the energy needs of cargo handling equipment, whether they are all-electric, hydrogen fuel cell, or powered by another fuel-type. Zero and near-zero emission fuel supply at ports is evaluated looking into the characteristics of hydrogen, ammonia, and methanol as an alternative fuel, as well as the bunkering status. The readiness of reference ports to produce ammonia or methanol and bunker the fuel is examined based on the framework developed by the Global Maritime Forum and Rocky Mountain Institute.

08 HYDROGEN↗
DOE OSTI2020

Remaining Useful Strength (RUS) Prediction of SiCf-SiCm Composite Materials Using Deep Learning and Acoustic Emission

Prognosis techniques for prediction of remaining useful life (RUL) are of crucial importance to the management of complex systems for they can lead to appropriate maintenance interventions and improvements in reliability. While various data-driven methods have been introduced to predict the remaining useful life (RUL) of machinery systems or batteries, no research has been reported on the remaining useful strength (RUS) prediction of silicon carbide fiber reinforced silicon carbide matrix (SiCf-SiCm) materials with pivotal role in its potential usage as a structural material in nuclear reactors and turbine engines. Knowledge of its degradation process is of the utmost importance to the manufacturers. For this purpose, two approaches based on the machine-learning techniques of random-forest (RF) and convolutional neural network (CNN) are proposed to predict the RUS of SiCf-SiCm using only acoustic emission (AE) signals generated during the material’s stress applying process. Experimental results show that the CNN models achieved better predictive performance than the RF models but the latter with expert-engineered features achieves better prediction for AE signals in the early stage of degradation. Additionally, our results demonstrate that both models can correctly predict the SiCf-SiCm RUS as evaluated by our robust testing method from which the best average root mean square error (RMSE) and Pearson correlation coefficient of 3.55 ksi units and 0.85 were obtained.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Mathematical modeling in cancer nanomedicine: a review

Cancer continues to be among the leading healthcare problems worldwide, and efforts continue not just to find better drugs, but also better drug delivery methods. The need for delivering cytotoxic agents selectively to cancerous cells, for improved safety and efficacy, has triggered the application of nanotechnology in medicine. This effort has provided drug delivery systems that can potentially revolutionize cancer treatment. Nanocarriers, due to their capacity for targeted drug delivery, can shift the balance of cytotoxicity from healthy to cancerous cells. The field of cancer nanomedicine has made significant progress, but challenges remain that impede its clinical translation. Several biophysical barriers to the transport of nanocarriers to the tumor exist, and a much deeper understanding of nano-bio interactions is necessary to change the status quo. Mathematical modeling has been instrumental in improving our understanding of the physicochemical and physiological underpinnings of nanomaterial behavior in biological systems. Here, we present a comprehensive review of literature on mathematical modeling works that have been and are being employed towards a better understanding of nano-bio interactions for improved tumor delivery efficacy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Energy modeling and efficiency analysis of aluminum die-casting processes

Energy modeling and efficiency analysis are considered the foundation of manufacturing process optimization to improve quality and efficiency and reduce energy consumption and carbon emissions during aluminum die-casting processes. Our report introduced an energy modeling method to connect gas and electric energy consumption with production rate of aluminum die-casting processes based on data collected at workshops with various combination of machines and products. The detailed modeling process involved the development of a data-acquiring system and the comparison of various kinds of nonlinear regression methods. The resulting models were confirmed with actual production data and were also used to improve production scheduling. Furthermore, it was found that if the modeling results are reasonably used and production is accordingly well-scheduled, 10 to 15% of energy savings could be realized without sacrificing profits.

42 ENGINEERING↗
DOE OSTI2021

DART-PFLOTRAN: An ensemble-based data assimilation system for estimating subsurface flow and transport model parameters

Ensemble-based Data Assimilation (EDA), based on the Monte Carlo approach, has been effectively applied to estimate model parameters through inverse modeling in subsurface flow and transport problems. However, implementation of EDA approach involves a complicated workflow that include setting up and executing ensemble forward model simulations, processing observations and model simulation results for parameter updates, and repeat for sequential or iterative EDA. To facilitate the management of such workflow and lower the barriers for adopting EDA-based parameter estimation in subsurface science, we develop a generic software frame-work linking the Data Assimilation Research Testbed (DART) with a massively parallel subsurface FLOw and TRANsport code PFLOTRAN. The new DART-PFLOTRAN leverages both the core data assimilation engines in DART and the computational power afforded by PFLOTRAN. In addition to the standard smoother and filtering options, DART-PFLOTRAN enables an iterative EDA workflow based on the Ensemble Smoother for Multiple Data Assimilation method (ES-MDA) to improve estimation accuracy for nonlinear forward problems. Here, we verify the implementation of ES-MDA in DART-PFLOTRAN using two synthetic cases designed to estimate static permeability and dynamic exchange fluxes across the riverbed, respectively, from continuous temperature measurements made across a depth profile. One-dimensional hydro-thermal simulations are performed in both cases to relate temperature responses with the parameters of interest. In the case of estimating dynamic parameters, we demonstrate the flexibility of DART-PFLOTRAN in automating sequential ES-MDA workflow, which will significantly reduce the time researchers spend on managing complex workflows in similar applications. Both studies yield accurate estimations of the parameters compared to their synthetic truth, while ES-MDA leads to more accurate estimation when a high level of nonlinearity exist between observed responses and unknown parameters. With a code base in Python and Fortran, DART-PFLOTRAN paves the way for applications in large-scale subsurface inverse modeling by automating the complex workflow of sequential ES-MDA that can be executed on various computing platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Development of Community, Capabilities and Understanding Through Unmanned Aircraft-Based Atmospheric Research: The LAPSE-RATE Campaign

Members of the international community developing unmanned aircraft for atmospheric research conducted a highly-successful coordinated flight week in Colorado during summer 2018 to collect measurements, develop capabilities, and enhance community in the field. Because unmanned aircraft systems (UAS) offer new perspectives on the atmosphere, their use in atmospheric science is expanding rapidly. In support of this growth, the International Society for Atmospheric Research using Remotely-piloted Aircraft (ISARRA) has been developed and have convened annual meetings and 'flight weeks'. The 2018 flight week, dubbed the Lower Atmospheric Profiling Studies at Elevation - a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE), involved a one-week deployment to Colorado's San Luis Valley. Between 14-20 July 2018 over 100 students, scientists, engineers, pilots and outreach coordinators conducted an intensive field operation using unmanned aircraft and ground-based assets to develop datasets, community, and capabilities. In addition to a coordinated 'community day' which offered a chance for groups to share their aircraft and science with the San Luis Valley community, LAPSE-RATE participants conducted nearly 1300 research flights totaling over 250 flight hours. The measurements collected have been used to advance capabilities (instrumentation, platforms, sampling techniques and modeling tools), conduct a detailed system intercomparison study, develop new collaborations, and foster community support for the use of UAS in atmospheric science.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Environmental Protection Coating System for Refractory Metal Alloys (EPCS for RMAs)

As part of ARPA-E’s Ultra High Temperature Impervious Materials Advancing Turbine Efficiency (UITIMATE) program, this project aims to develop an environmental protection coating system (EPCS) for refractory metal alloys (RMAs) – which will provide radical improvement in long term protection for ultra-high temperature refractory metal components in harsh gas-turbine environments. The drive for higher fuel efficiency and higher core power of gas turbines used in electric power generation and in aircraft propulsion requires higher peak operation temperatures. The temperature capability of state-of-the-art materials cannot meet the new requirements. Refractory metal alloys have desirable capabilities for achieving the required peak temperatures, but most of them are subject to oxidation in the gas turbine environment. Thus, there is a strong need to develop novel environmental protective coatings that enable the refractory metals to operate in an ultra-high temperature engine environment. This project is composed of four major technical innovations that can provide a potentially transformational solution in providing environmental protection for refractory metal alloys over a wide range of temperature. 1) Multi-layer self-healing environmental barrier coating (EBC) that provides protection against combustion gas environment. 2) Oxidation resistant diffusion barrier (DB) on the alloy surface to enhance coating stability. 3) Synergistic integration of the multi-layer self-healing EBC with the diffusion barrier to extend coating life. 4) Guidance of physics-based modeling to accelerate coating development and optimization. Our team has successfully developed a multi-layer self-healing environmental protection coating system (EPCS) that can provide oxidation protection for commercially available molybdenum based refractory metal alloys over a wide temperature range of up to 1600 °C for fuel-efficient gas turbine applications. The team also developed a multi-layer high temperature coating design tool to accelerate coating development and optimization based on physics-based modeling. The team also engaged RTX business unite, notable Pratt and Whitney, for future commercialization of this technology. The successful completion of this Phase I effort led to the selection of performing Phase II of the program. In Phase II, the team plans to apply the EPCS in the protection of a newly discovered molybdenum-based metal alloy which has the potential of superior high temperature properties to the commercial products. Th coating will be evaluated under test conditions and environment that mimic gas turbine operation.

36 MATERIALS SCIENCE↗