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At least 955 records · Page 53

Modeling the U.S. Western Electric Interconnection to Understand the Consequences of Hydrometeorological Extremes and Options for Risk Mitigation

Electricity grid operators around the world face a dual challenge; withstanding increasingly severe weather and the longer term impacts of climate change, while simultaneously decarbonizing. Extreme weather events such as heat waves and droughts are rising in both severity and frequency, which is threatening the reliability of electricity grids through increased demand, generation capacity losses, and equipment failures. Consequently, incorporating hydrometeorological stressors into computational power systems analysis is becoming an even more critical tool in long term planning and short term operations. However, there is a general lack of open-source customizable grid simulation software capable of exhaustively stress testing the grid under hydrometeorological uncertainty, and/or examining potential risk mitigation pathways. A related, persistent challenge for power system modelers is striking an appropriate balance between model fidelity (e.g. spatial scale and time resolution) and computational tractability (wall clock run-time). In this study, we are proposing a solution to this problem with open-source software that allows users to seamlessly customize the scale and track the accuracy of grid operations models. Our approach allows users to search over numerous model parameters (network topology, mathematical formulation, economic hurdle rates, and transmission line scaling) to identify model instantiations that accommodate experimental design. Further, we use this approach to demonstrate the importance of including extreme weather events in model validation and model selection. Focusing on the occurrence of heatwaves and droughts in the U.S. Western Interconnection, we examine role of extreme events in balancing tradeoffs between model fidelity and run-time at the model design stage.

Economics↗

Cryogenic thermal modeling of microwave high density signaling

Superconducting quantum computers require microwave control lines running from room temperature to the mixing chamber of a dilution refrigerator. Adding more lines without preliminary thermal modeling to make predictions risks overwhelming the cooling power at each thermal stage. In this paper, we investigate the thermal load of SC-086/50-SCN-CN semi-rigid coaxial cable, which is commonly used for the control and readout lines of a superconducting quantum computer, as we increase the number of lines to a quantum processor. We investigate the makeup of the coaxial cables, verify the materials and dimensions, and experimentally measure the total thermal conductivity of a single cable as a function of the temperature from cryogenic to room temperature values. We also measure the cryogenic DC electrical resistance of the inner conductor as a function of temperature, allowing for the calculation of active thermal loads due to Ohmic heating. Fitting this data produces a numerical thermal conductivity function used to calculate the static heat loads due to thermal transfer within the wires resulting from a temperature gradient. The resistivity data is used to calculate active heat loads, and we use these fits in a cryogenic model of a superconducting quantum processor in a typical Bluefors XLD1000-SL dilution refrigerator, investigating how the thermal load increases with processor sizes ranging from 100 to 225 qubits. We conclude that the theoretical upper limit of the described architecture is approximately 200 qubits. However, including an engineering margin in the cooling power and the available space for microwave readout circuitry at the mixing chamber, the practical limit is approximately 140 qubits.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Using Satellite Soil Moisture and Rainfall in the Landslide Hazard Assessment for Situational Awareness System

The Landslide Hazard Assessment for Situational Awareness system(LHASA)gives a global view of landslide hazard in nearly real time. Currently, it is being upgraded from version 1 to version 2, which entails improvements along several dimensions. These include the incorporation of new predictors, machine learning, and new event-based landslide inventories. As a result, LHASA version 2 substantially improves on the prior performanceand introduces a probabilistic element to the global landslide nowcast. Data from the soil moisture active-passive (SMAP) satellite has been assimilated into a globally consistent data product with a latency less than 3 days, known as SMAP Level 4. In LHASA, thesedata representthe antecedent conditions prior to landslide-triggering rainfall. In some cases, soil moisture may have accumulated over aperiod of many months. The model behind SMAP Level 4 also estimates the amount of snow on the ground, which is an important factor in some landslide events. LHASA also incorporates this information as an antecedent condition that modulates the response torainfall. Slope, lithology, and active faults were also used as predictor variables. These factors can have a strong influence on where landslides initiate.LHASA relies on precipitation estimates from the Global Precipitation Measurement mission to identify the locations where landslides are most probable. The low latency and consistent global coverage of these data make them ideal for real-time applications at continental to global scales. LHASA relies primarily on rainfall from the last 24 hours to spothazardous sites, which is rescaled by the local 99thpercentile rainfall.However, the multi-day latency of SMAP requires the use of a 2-day antecedent rainfall variable to represent the accumulation of rain between the antecedent soil moisture and current rainfall. LHASA merges these predictors with XGBoost, a commonly used machine-learning tool, relying on historical landslide inventories to develop the relationship between landslide occurrence and various risk factors. The resulting model relies heavily on current daily rainfall, but other factors also play an important role. LHASA outputsthe probability oflandslide occurrence ona grid of roughly one kilometer over all continents from 60 North to 60 South latitude. Evaluation over the period 2019-2020 showsthat LHASA version 2 doubles the accuracy of the global landslide nowcast without increasing the global false alarm rate. LHASA also identifies the areas where the human exposure to landslide hazard is most intense. Landslide hazard is divided into 4 levels: minimal, low, moderate, and high. Next, the number of persons and the length of major roads (primary and secondary roads)within each of these areas is calculated for every second-level administrative district (county). These results can be viewedthrough a web portal hosted at the Goddard Space Flight Center. In addition, users can download daily hazard and exposure data.LHASAversion 2uses machine learning and satellite data to identify areas of probable landslide hazard within hours of heavy rainfall. Itsglobal maps are significantly more accurate, and it now includes rapid estimates of exposed populations and infrastructure. In addition, a forecast mode will be implemented soon.

Thomas Stanley↗

Cancer Risk Assessment for Space Radiation

Predicting the occurrence of human cancer following exposure to any agent causing genetic damage is a difficult task. This is because the uncertainty of uniform exposure to the damaging agent, and the uncertainty of uniform processing of that damage within a complex set of biological variables, degrade the confidence of predicting the delayed expression of cancer as a relatively rare event within any given clinically normal individual. The radiation health research priorities for enabling long-duration human exploration of space were established in the 1996 NRC Report entitled "Radiation Hazards to Crews of Interplanetary Missions: Biological Issues and Research Strategies". This report emphasized that a 15-fold uncertainty in predicting radiation-induced cancer incidence must be reduced before NASA can commit humans to extended interplanetary missions. That report concluded that the great majority of this uncertainty is biologically based, while a minority is physically based due to uncertainties in radiation dosimetry and radiation transport codes. Since that report, the biologically based uncertainty has remained large, and the relatively small uncertainty associated with radiation dosimetry has increased due to the considerations raised by concepts of microdosimetry. In a practical sense, however, the additional uncertainties introduced by microdosimetry are encouraging since they are in a direction of lowered effective dose absorbed through infrequent interactions of any given cell with the high energy particle component of space radiation. The biological uncertainty in predicting cancer risk for space radiation derives from two primary facts. 1) One animal tumor study has been reported that includes a relevant spectrum of particle radiation energies, and that is the Harderian gland model in mice. Fact #1: Extension of cancer risk from animal models, and especially from a single study in an animal model, to humans is inherently uncertain. 2) One human database is predominantly used for assessing cancer risk caused by space radiation, and that is the Japanese atomic bomb survivors. Fact #2: The atomic-bomb-survivor database, itself a remarkable achievement, contains uncertainties. These include the actual exposure to each individual, the radiation quality of that exposure, and the fact that the exposure was to acute doses of predominantly low-LET radiation, not to chronic exposures of high-LET radiation expected on long-duration interplanetary manned missions.

Richmond, Robert C.↗

Advanced risk assessment of the effects of graphite fibers on electronic and electric equipment, phase 1

A model was developed to generate quantitative estimates of the risk associated with the release of graphite fibers during fires involving commercial aircraft constructed with graphite fiber composite materials. The model was used to estimate the risk associated with accidents at several U.S. airports. These results were then combined to provide an estimate of the total risk to the nation.

Pocinki, L. S.↗

Radiation Physics for Space and High Altitude Air Travel

Galactic cosmic rays (GCR) are of extra-solar origin consisting of high-energy hydrogen, helium, and heavy ions. The GCR are modified by physical processes as they traverse through the solar system, spacecraft shielding, atmospheres, and tissues producing copious amounts of secondary radiation including fragmentation products, neutrons, mesons, and muons. We discuss physical models and measurements relevant for estimating biological risks in space and high-altitude air travel. Ambient and internal spacecraft computational models for the International Space Station and a Mars mission are discussed. Risk assessment is traditionally based on linear addition of components. We discuss alternative models that include stochastic treatments of columnar damage by heavy ion tracks and multi-cellular damage following nuclear fragmentation in tissue.

Cucinotta, F. A.↗

Understanding Earthquake Fault Systems Using QuakeSim Analysis and Data Assimilation Tools

We are using the QuakeSim environment to model interacting fault systems. One goal of QuakeSim is to prepare for the large volumes of data that spaceborne missions such as DESDynI will produce. QuakeSim has the ability to ingest distributed heterogenous data in the form of InSAR, GPS, seismicity, and fault data into various earthquake modeling applications, automating the analysis when possible. Virtual California simulates interacting faults in California. We can compare output from long time history Virtual California runs with the current state of strain and the strain history in California. In addition to spaceborne data we will begin assimilating data from UAVSAR airborne flights over the San Francisco Bay Area, the Transverse Ranges, and the Salton Trough. Results of the models are important for understanding future earthquake risk and for providing decision support following earthquakes. Improved models require this sensor web of different data sources, and a modeling environment for understanding the combined data.

earthquake simulations↗

Considerations When Building Thermal Models that Require Conversion Between Formats

At times, it is inevitable to require conversion of thermal models from one software format to another. This most often occurs for missions with international partners where not all parties utilize the same software packages for thermal analysis. Mandating a single tool for all parties is one possible solution, but this approach can introduce problems if significant effort is required to overcome inexperience with the designated tool and may result in difficulty meeting analysis schedule requirements. Alternatively, allowing all parties to use their own familiar tools minimizes the impact to analysis schedules but does introduce the need to convert the models later to a common format for analysis at a higher level of assembly. External conversion tools and formats have been developed through the years to aid in this process, but have had limited success in fully converting models seamlessly. Having a basic familiarity with tool capabilities on both sides of the conversion process allows for models to be built in a manner to better facilitate conversion by avoiding features and capabilities which are unsupported by the destination tool or for which no workarounds exist. Also, the effort to convert a model is often neglected when developing the schedules for analysis at the higher assembly levels; delivery of models preconditioned for convertibility minimizes the schedule risk. This paper seeks to provide some guidance on modeling techniques to avoid when developing Geometrical Math Models (GMM) and Thermal Math Models (TMM) when conversion is required. The recommendations are based on GMM conversion experiences between TSS/ThermalDesktop/ESARAD and TMM conversions between SINDA-FLUINT/ESATAN.

Modeling↗

Sensor Analysis, Modeling, and Test for Robust Propulsion System Autonomy

An approach is presented supporting analysis, modeling, and test validation of operational flight instrumentation (OFI) that facilitates critical functions for the Space Launch System (SLS) main propulsion system (MPS). Certain types of OFI sensors were shown to exhibit highly nonlinear and non-gaussian noise characteristics during acceptance testing, motivating the development of advanced modeling and simulation (M&S) capability to support algorithm verification and flight certification. Hardware model and algorithm simulation fidelity was informed by a risk scoring metric; redesign of high-risk algorithms using test-validated sensor models significantly improved their expected performance as evaluated using Monte Carlo acceptance sampling methods. Autonomous functions include closed-loop ullage pressure regulation, pressurant leak detection, and fault isolation for automated safing and crew caution and warning (C&W).

Orr, Jeb S.↗

Effect of Clouds on Optical Imaging of the Space Shuttle During the Ascent Phase: A Statistical Analysis Based on a 3D Model

Clouds are highly effective in obscuring optical images of the Space Shuttle taken during its ascent by ground-based and airborne tracking cameras. Because the imagery is used for quick-look and post-flight engineering analysis, the Columbia Accident Investigation Board (CAIB) recommended the return-to-flight effort include an upgrade of the imaging system to enable it to obtain at least three useful views of the Shuttle from lift-off to at least solid rocket booster (SRB) separation (NASA 2003). The lifetimes of individual cloud elements capable of obscuring optical views of the Shuttle are typically 20 minutes or less. Therefore, accurately observing and forecasting cloud obscuration over an extended network of cameras poses an unprecedented challenge for the current state of observational and modeling techniques. In addition, even the best numerical simulations based on real observations will never reach "truth." In order to quantify the risk that clouds would obscure optical imagery of the Shuttle, a 3D model to calculate probabilistic risk was developed. The model was used to estimate the ability of a network of optical imaging cameras to obtain at least N simultaneous views of the Shuttle from lift-off to SRB separation in the presence of an idealized, randomized cloud field.

FROM↗

Grand challenges in the design, manufacture, and operation of future wind turbine systems

Abstract. Wind energy is foundational for achieving 100 % renewable electricity production, and significant innovation is required as the grid expands and accommodates hybrid plant systems, energy-intensive products such as fuels, and a transitioning transportation sector. The sizable investments required for wind power plant development and integration make the financial and operational risks of change very high in all applications but especially offshore. Dependence on a high level of modeling and simulation accuracy to mitigate risk and ensure operational performance is essential. Therefore, the modeling chain from the large-scale inflow down to the material microstructure, and all the steps in between, needs to predict how the wind turbine system will respond and perform to allow innovative solutions to enter commercial application. Critical unknowns in the design, manufacturing, and operability of future turbine and plant systems are articulated, and recommendations for research action are laid out. This article focuses on the many unknowns that affect the ability to push the frontiers in the design of turbine and plant systems. Modern turbine rotors operate through the entire atmospheric boundary layer, outside the bounds of historic design assumptions, which requires reassessing design processes and approaches. Traditional aerodynamics and aeroelastic modeling approaches are pressing against the limits of applicability for the size and flexibility of future architectures and flow physics fundamentals. Offshore wind turbines have additional motion and hydrodynamic load drivers that are formidable modeling challenges. Uncertainty in turbine wakes complicates structural loading and energy production estimates, both around a single plant and for downstream plants, which requires innovation in plant operations and flow control to achieve full energy capture and load alleviation potential. Opportunities in co-design can bring controls upstream into design optimization if captured in design-level models of the physical phenomena. It is a research challenge to integrate improved materials into the manufacture of ever-larger components while maintaining quality and reducing cost. High-performance computing used in high-fidelity, physics-resolving simulations offer opportunities to improve design tools through artificial intelligence and machine learning, but even the high-fidelity tools are yet to be fully validated. Finally, key actions needed to continue the progress of wind energy technology toward even lower cost and greater functionality are recommended.

17 WIND ENERGY↗

ORDEM 3.0 and the Risk of High-Density Debris

NASA’s Orbital Debris Engineering Model was designed to calculate orbital debris fluxes on spacecraft in order to assess collision risk. The newest of these models, ORDEM 3.0, has a number of features not present in previous models. One of the most important is that the populations and fluxes are now broken out into material density groups. Previous models concentrated on debris size alone, but a particle’s mass and density also determine the amount of damage it can cause. ORDEM 3.0 includes a high-density component, primarily consisting of iron/steel particles that drive much of the risk to spacecraft. This paper will outline the methods that were used to separate and identify the different densities of debris, and how these new densities affect the overall debris flux and risk.

Matney, Mark↗

Mapping by VESGEN of Blood Vessels in the Retinas of Astronauts Pre- and Post-Flight to the ISS

Research by NASA [1] established that significant risks for visual and ocular impairments associated with increased intracranial pressure (VIIP) are incurred by microgravity spaceflight, especially long-duration missions. It is well established in physiology and pathology that a fundamental role of the microvasculature is to mediate fluid transfers and remodel actively in response to environmental, immune and other stresses. We therefore hypothesize that remodeling of retinal blood vessels necessarily occurs during accommodation of microgravity-induced fluid shifts prior to subsequent development of visual and ocular impairments. Potential contributions of retinal vascular remodeling to VIIP etiology are therefore being investigated by NASA's innovative VESsel GENeration Analysis (VESGEN) software for two studies: (1) U.S. crew members before and after ISS missions, and (2) head-down tilt in human subjects before and after 70 days of bed rest. We anticipate that results of the two studies will be complete by the Investigators Workshop (January 22, 2017). METHODS: For the 2013 NASA NRA award, we are concluding the analysis of 30 degree infrared (IR) Heidelberg Spectralis images of retinal blood vessels by VESGEN (patents pending), a mature, automated software developed as a translational and basic vascular research discovery tool, particularly for retinal vascular disease. Subjects of our retrospective study include eight ISS crew members monitored for routine occupational surveillance pre- and post-flight, who provided their study consents to NASAs Lifetime Surveillance of Astronaut Health (LSAH) in coordination with approval of the VESGEN retrospective study protocol by NASAs Institutional Review Board (IRB). The ophthalmic retinal images (average image resolution, approximately 5.6 microns per pixel) are blinded as to pre and post ISS status until the second portion of our study, when VESGEN results will be correlated with other ophthalmic and medical findings for the crew members. Due to image resolution challenges, a novel Matlab tool was developed for aligning pre and post images, and comparing (querying) the two images for differences in the morphology of small vessels. RESULTS: During the past year, LSAH approved the release of all astronaut retinal images to our study for VESGEN analysis. Substantial progress on the initial blinded portion of the study is in place. We anticipate that VESGEN analysis of the 32 Spectralis IR retinal images will be complete for presentation at the 2017 IWS meeting. CONCLUSIONS: Modified retinal vascular patterning may offer early-stage predictions of ocular changes resulting in decreased visual acuity for the VIIP syndrome. Novel insights provided by VESGEN into progressively pathological and blinding vascular remodeling in the human retina currently help to guide other NIH- and NASA-supported therapeutic studies of retinal disease and modeling of the VIIP risk. Results of our vascular investigation of the retinas of astronauts pre- and post-flight may help advance the understanding of both healthy and pathological adaptations to fluid shifts in microgravity associated with the VIIP syndrome. Preliminary results indicate that imaging of higher resolution, such as the new OCT angiography (OCT-A) technology, will be required to determine conclusively the role of the smaller retinal and choroidal vessels in VIIP etiology.

VESGEN↗

Single track effects, Biostack and risk assessment

The scientific career of Prof. Bucker has spanned a very exciting period in the fledgling science of Space Radiation Biology. The capability for placing biological objects in space was developed, and the methods for properly packaging, retrieving and analyzing them were worked out. Meaningful results on the effects of radiation were obtained for the first time. In fact, many of the successful techniques and methodologies for handling biological samples were developed in Prof. Bucker's laboratories, as attested by the extensive Biostack program. He was the first to suggest and successfully carry out experiments in space directly aimed at measuring effects of single tracks of high-energy heavy galactic cosmic rays by specifically identifying whether or not the object had been hit by a heavy particle track. Because the "hit" frequencies of heavy galactic cosmic rays to cell nuclei in the bodies of space travelers will be low, it is expected that any effects to humans on the cellular level will be dominated by single-track cell traversals. This includes the most important generally recognized late effect of space radiation exposure: radiation-induced cancer. This paper addresses the single-track nature of the space radiation environment, and points out the importance of single "hits" in the evaluation of radiation risk for long-term missions occurring outside the earth's magnetic field. A short review is made of biological objects found to show increased effects when "hit" by a single heavy charged-particle in space. A brief discussion is given of the most provocative results from the bacterial spore Bacillus subtilis: experimental evidence that tracks can affect biological systems at much larger distances from the trajectory than previously suspected, and that the resultant inactivation cross section in space calculated for this system is very large. When taken at face value, the implication of these results, when compared to those from experiments performed at ground-based accelerators with beams at low energies in the same LET range, is that high-energy particles can exert their influence a surprising distance from their trajectory and the inactivation cross sections are some 20 times larger than expected. Clearly, beams from high-energy heavy-ion accelerators should be used to confirm these results. For those end points that can also be caused by low-LET beams such as high-energy protons, it is important to measure their action cross sections as well. The ratio of the cross sections for a high-LET beam to that of a low-LET beam is an interesting experimental ratio and, we suggest, of more intrinsic interest than the RBE (Relative Biological Effectiveness). It is a measure of the "biological" importance of one particle type relative to another particle type. This ratio will be introduced and given the name RPPE (Relative Per Particle Effectiveness). Values of RPPE have appeared in the literature and will be discussed. A rather well-known value of this quantity (13,520) has been suggested for the RPPE of high-energy iron ions to high-energy protons. This value was suggested by Letaw et al. Nature 330, 709-710 (1987)] we will call it the Letaw limit. It will be discussed in terms of the importance of the heavy-ion component vs light-ion component of the galactic cosmic rays. It is also pointed out, however, that there may be unique effects from single tracks of heavy ions that do not occur from light-ion tracks. For such effects, the concepts of both RBE and RPPE lose their meaning.

NASA Discipline Radiation Health↗

Safety Metrics for Human-Computer Controlled Systems

The rapid growth of computer technology and innovation has played a significant role in the rise of computer automation of human tasks in modem production systems across all industries. Although the rationale for automation has been to eliminate "human error" or to relieve humans from manual repetitive tasks, various computer-related hazards and accidents have emerged as a direct result of increased system complexity attributed to computer automation. The risk assessment techniques utilized for electromechanical systems are not suitable for today's software-intensive systems or complex human-computer controlled systems.This thesis will propose a new systemic model-based framework for analyzing risk in safety-critical systems where both computers and humans are controlling safety-critical functions. A new systems accident model will be developed based upon modem systems theory and human cognitive processes to better characterize system accidents, the role of human operators, and the influence of software in its direct control of significant system functions Better risk assessments will then be achievable through the application of this new framework to complex human-computer controlled systems.

Leveson, Nancy G↗

Renewable electricity capacity planning with uncertainty at multiple scales

Abstract We formulate and compare optimization models of investment in renewable generation using a suite of social planning models that compute optimal generation capacity investments for a hydro-dominated electricity system where inflow uncertainty results in a risk of energy shortage. The models optimize the expected cost of capacity expansion and operation allowing for investments in hydro, geothermal, solar, wind, and thermal plant, as well as battery storage for smoothing load profiles. A novel feature is the integration of uncertain seasonal hydroelectric energy supply and short-term variability in renewable supply in a two-stage stochastic programming framework. The models are applied to data from the New Zealand electricity system and used to estimate the costs of moving to a 100% renewable electricity system by 2035. We also explore the outcomes obtained when applying different forms of CO 2 constraint that limit respectively non-renewable capacity, non-renewable generation, and CO 2 emissions on average, almost surely, or in a chance-constrained setting, and show how our models can be used to investigate the merits of a proposed pumped-hydro scheme in New Zealand’s South Island.

Ferris, Michael C.↗

Overview of the physics basis for the ARC fusion power plant

Commonwealth Fusion Systems plans to build ARC as the first fusion power plant at a site in Chesterfield County, Virginia, USA by the early 2030s. We present an overview of analysis comprising the physics basis of the ARC V3A design, a high-magnetic-field tokamak with 𝐵 0 =11.4 T, 𝐼 𝑝 =12.0 MA, 𝑅 0 =4.62 m, 𝑎 =1.18 m. ARC V3A is designed to produce 𝑃 𝑓⁡𝑢⁢𝑠 ≈1.13 GW DT fusion power and deliver ⩾400 MW net electric power to the grid. This overview includes quantitative analysis of fundamental issues for design of and operational plasma scenarios for a tokamak power plant, and lays out the design targets and strategic choices for ARC, including empirical fusion performance projections, assessment of H-mode access, ion cyclotron resonance heating simulations, alpha particle physics and time-dependent full-pulse simulations. This is complemented by topical papers on fusion performance and transport, disruption physics, boundary physics and magnetohydrodynamic stability. Critically, these studies identify key model uncertainties and physics risks to be retired through SPARC operation. Due to the modular nature of ARC, early results from SPARC can be incorporated into the design of the first ARC as well as subsequent replacements of the ARC vacuum vessel.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

MultiSector Dynamics: Advancing the Science of Complex Adaptive Human-Earth Systems

The field of MultiSector Dynamics (MSD) explores the dynamics and co-evolutionary pathways of human and Earth systems with a focus on critical goods, services, and amenities delivered to people through interdependent sectors. This commentary lays out core definitions and concepts, identifies MSD science questions in the context of the current state of knowledge, and describes ongoing activities to expand capacities for open science, leverage revolutions in data and computing, and grow and diversify the MSD workforce. Central to our vision is the ambition of advancing the next generation of complex adaptive human-Earth systems science to better address interconnected risks, increase resilience, and improve sustainability. This will require convergent research and the integration of ideas and methods from multiple disciplines. Understanding the tradeoffs, synergies, and complexities that exist in coupled human-Earth systems is particularly important in the context of energy transitions and increased future shocks.

Reed, Patrick↗