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NASA NTRS1981

Performance calculations for 1000 MWe MHD/steam power plants

The effects of MHD generator operating conditions and constraints on the performance of MHD/steam power plants are investigated. Power plants using high temperature combustion air preheat (2500 F) and plants using intermediate temperature preheat (1100 F) with oxygen enrichment are considered. Variations of these two types of power plants are compared on the basis of fixed total electrical output (1000 MWe). Results are presented to show the effects of generator plant length and level of oxygen enrichment on the plant thermodynamic efficiency and on the required generator mass flow rate. Factors affecting the optimum levels of oxygen enrichment are analyzed. It is shown that oxygen enrichment can reduce magnet stored energy requirement.

Pian, C. C. P.↗

NASA NTRS1999

A Spreadsheet Simulation Tool for Terrestrial and Planetary Balloon Design

During the early stages of new balloon design and development, it is necessary to conduct many trade studies. These trade studies are required to determine the design space, and aid significantly in determining overall feasibility. Numerous point designs then need to be generated as details of payloads, materials, mission, and manufacturing are determined. To accomplish these numerous designs, transient models are both unnecessary and time intensive. A steady state model that uses appropriate design inputs to generate system-level descriptive parameters can be very flexible and fast. Just such a steady state model has been developed and has been used during both the MABS 2001 Mars balloon study and the Ultra Long Duration Balloon Project. Using Microsoft Excel's built-in iteration routine, a model was built. Separate sheets were used for performance, structural design, materials, and thermal analysis as well as input and output sheets. As can be seen from figure 1, the model takes basic performance requirements, weight estimates, design parameters, and environmental conditions and generates a system level balloon design. Figure 2 shows a sample output of the model. By changing the inputs and a few of the equations in the model, balloons on earth or other planets can be modeled. There are currently several variations of the model for terrestrial and Mars balloons, as well there are versions of the model that perform crude material design based on strength and weight requirements. To perform trade studies, the Visual Basic language built into Excel was used to create an automated matrix of designs. This trade study module allows a three dimensional trade surface to be generated by using a series of values for any two design variables. Once the fixed and variable inputs are defined, the model automatically steps through the input matrix and fills a spreadsheet with the resulting point designs. The proposed paper will describe the model in detail, including current variations. The assumptions, governing equations, and capabilities will be addressed. Detailed examples of the model in practice will also be used.

Raquea, Steven M.↗

NASA NTRS2003

Effects of Fiber Reinforcement Architecture on the Hygrothermal-Mechanical Performance of Polyimide Matrix Composites for Aeropropulsion Applications

A lightweight sandwich support structure, for the combustor chamber of a new generation liquid propellant rocket engine, was designed and fabricated using a polymer matrix composite (PMC) facesheet on a Ti honeycomb core. The PMC facesheet consisted of high stiffness carbon fiber, M40JB, and high temperature Polyimides, such as PMR-II-50 and HFPE-II-52. Six different fiber architectures; four harness satin (4HS) woven fabric, uni-tape, woven-uni hybrid, stitched woven fabric, stitched uni-tape and triaxial braided structures have been investigated for optimum stiffness-thickness-weight-hygrothermal performance design criteria for the hygrothermal-mechanical propulsion service exposure conditions including rapid heating up to 200 F/sec, maximum operating temperature of 600 F, internal pressure up to 100 psi. One of the specific objectives in this study is to improve composite blistering resistance in z-direction at minimum expense of in-plane mechanical properties. An extensive property-performance database including dry-wet mechanical properties at various temperatures, thermal-physical properties, such as blistering onset condition was generated for fiber architecture down-selection and design guidelines. Various optimized process methods such as vacuum bag compression molding, solvent assistant resin transfer molding (SaRTM), resin film infusion (RFI) and autoclaving were utilized for PMC panel fabrication depending on the architecture type. In the case of stitched woven fabric architecture, the stitch pattern in terms of stitch density and yarn size was optimized based on both in-plane mechanical properties and blistering performance. Potential reduction of the in-plane properties transverse to the line of stitching was also evaluated. Efforts have been made to correlate the experimental results with theoretical micro-mechanics predictions. Changes in deformation mechanism and failure sequences in terms of fiber architecture will be discussed.

Shin, E. Eugene↗

NASA NTRS2016

NDARC NASA Design and Analysis of Rotorcraft - Input, Appendix 4

The NDARC code performs design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance analysis, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. The principal tasks (sizing, mission analysis, flight performance analysis) are shown in the figure as boxes with heavy borders. Heavy arrows show control of subordinate tasks. The aircraft description consists of all the information, input and derived, that denes the aircraft. The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. This information can be the result of the sizing task; can come entirely from input, for a fixed model; or can come from the sizing task in a previous case or previous job. The aircraft description information is available to all tasks and all solutions. The sizing task determines the dimensions, power, and weight of a rotorcraft that can perform a specified set of design conditions and missions. The aircraft size is characterized by parameters such as design gross weight, weight empty, rotor radius, and engine power available. The relations between dimensions, power, and weight generally require an iterative solution. From the design flight conditions and missions, the task can determine the total engine power or the rotor radius (or both power and radius can be fixed), as well as the design gross weight, maximum takeoff weight, drive system torque limit, and fuel tank capacity. For each propulsion group, the engine power or the rotor radius can be sized. Missions are defined for the sizing task, and for the mission performance analysis. A mission consists of a number of mission segments, for which time, distance, and fuel burn are evaluated. For the sizing task, certain missions are designated to be used for design gross weight calculations; for transmission sizing; and for fuel tank sizing. The mission parameters include mission takeoff gross weight and useful load. For specified takeoff fuel weight with adjustable segments, the mission time or distance is adjusted so the fuel required for the mission equals the takeoff fuel weight. The mission iteration is on fuel weight or energy. Flight conditions are specified for the sizing task, and for the flight performance analysis. For the sizing task, certain flight conditions are designated to be used for design gross weight calculations; for transmission sizing; for maximum takeoff weight calculations; and for anti-torque or auxiliary thrust rotor sizing. The flight condition parameters include gross weight and useful load. For flight conditions and mission takeoff, the gross weight can be maximized, such that the power required equals the power available. A flight state is defined for each mission segment and each flight condition. The aircraft performance can be analyzed for the specified state, or a maximum effort performance can be identified. The maximum effort is specified in terms of a quantity such as best endurance or best range, and a variable such as speed, rate of climb, or altitude.

Rotorcraft Input↗

NASA NTRS2018

Machine Learning Application to Atmospheric Chemistry Modeling

Atmospheric chemistry is a high-dimensionality, large-data problem and thus may be suited to machine-learning algorithms. We show here the potential of a random forest regression algorithm to replace the gas-phase chemistry solver in the GEOS-Chem chemistry model. In this proof-of-concept study, we used one month of model output to train random forest regression models to predict the concentrations of each long-lived chemical species after integration based upon the physical and chemical conditions before the chemical integration. The choice of prediction type has a strong impact on the skill of the regression model. We find best results from predicting the change in concentration for very long-lived species and the absolute concentration for shorter lived species. The skill of the machine learning algorithm is further improved by using a family approach for NO and NO2 rather than treating them independently.By replacing the numerical integrator with the random forest algorithm and running this model for one month, we find that the model is able to reproduce many of the features of the reference chemistry simulation. Replacing the integration methodology with a machine learning algorithm has the potential to be substantially faster. There are a wide range of applications for such an approach, e.g. to generate boundary conditions, for use in air quality forecasts or chemical data assimilation systems, etc.

Keller, Christoph A.↗

NASA NTRS1991

Local Synthesis and Tooth Contact Analysis of Face-Milled Spiral Bevel Gears

Computerized simulation of meshing and bearing contact for spiral bevel gears and hypoid gears is a significant achievement that could substantially improve the technology and the quality of the gears. An approach to the synthesis of face-milled spiral bevel gears and their tooth contact analysis is presented. The proposed approach is based on the following ideas: application of the principle of local synthesis that provides optimal conditions of meshing and contact at the mean contact point, M, and in the neighborhood of M; and application of relations between principle directions and curvatures for surfaces being in line contact or in point contact. The developed local synthesis of gears provides the following: (1) the required gear ratio at M; (2) a localized bearing contact with the desired direction of the tangent to the contact path on gear tooth surface and the desired length of the major axis of contact ellipse at M; (3) a predesigned parabolic function of a controlled level for transmission errors which enables absorption of linear functions of transmission errors caused by misalignment and reduces the level of vibrations. The proposed approach does not require either the tilt of the head-cutter for the process of generation or modified roll for the pinion generation. Improved conditions of meshing and contact of the gears can be achieved without the above mentioned parameters. A computer program for determination of basic machine-tool settings and tooth contact analysis for the designed gears is presented. The approach is illustrated with a numerical example.

Litvin, Faydor L.↗

NASA NTRS2022

NDARC - NASA Design and Analysis of Rotorcraft: Input and Data Structures - Vol 2

The NDARC code performs design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance analysis, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. Figure 1-1 illustrates the tasks. The principal tasks (sizing, mission analysis, flight performance analysis) are shown in the figure as boxes with heavy borders. Heavy arrows show control of subordinate tasks. The aircraft description (figure 1-1) consists of all the information, input and derived, that defines the aircraft. The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. This information can be the result of the sizing task; can come entirely from input, for a fixed model; or can come from the sizing task in a previous case or previous job. The aircraft description information is available to all tasks and all solutions (indicated by light arrows). The sizing task determines the dimensions, power, and weight of a rotorcraft that can perform a specified set of design conditions and missions. The aircraft size is characterized by parameters such as design gross weight, weight empty, rotor radius, and engine power available. The relations between dimensions, power, and weight generally require an iterative solution. From the design flight conditions and missions, the task can determine the total engine power or the rotor radius (or both power and radius can be fixed), as well as the design gross weight, maximum takeoff weight, drive system torque limit, and fuel tank capacity. For each propulsion group, the engine power or the rotor radius can be sized. Missions are defined for the sizing task, and for the mission performance analysis. A mission consists of a number of mission segments, for which time, distance, and fuel burn are evaluated. For the sizing task, certain missions are designated to be used for design gross weight calculations; for transmission sizing; and for fuel tank sizing. The mission parameters include mission takeoff gross weight and useful load. For specified takeoff fuel weight with adjustable segments, the mission time or distance is adjusted so the fuel required for the mission (burned plus reserve) equals the takeoff fuel weight. The mission iteration is on fuel weight or energy. Flight conditions are specified for the sizing task, and for the flight performance analysis. For the sizing task, certain flight conditions are designated to be used for design gross weight calculations; for transmission sizing; for maximum takeoff weight calculations; and for antitorque or auxiliary thrust rotor sizing. The flight condition parameters include gross weight and useful load. For flight conditions and mission takeoff, the gross weight can be maximized, such that the power required equals the power available. A flight state is defined for each mission segment and each flight condition. The aircraft performance can be analyzed for the specified state, or a maximum effort performance can be identified. The maximum effort is specified in terms of a quantity such as best endurance or best range, and a variable such as speed, rate of climb, or altitude. The aircraft must be trimmed, by solving for the controls and motion that produce equilibrium in the specified flight state. Different trim solution definitions are required for various flight states. Evaluating the rotor hub forces may require solution of the blade flap equations of motion.

NDARC↗

NASA NTRS2022

NDARC - NASA Design and Analysis of Rotorcraft: Input - Vol 3

The NDARC code performs design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance analysis, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. Figure 1-1 illustrates the tasks. The principal tasks (sizing, mission analysis, flight performance analysis) are shown in the figure as boxes with heavy borders. Heavy arrows show control of subordinate tasks. The aircraft description (figure 1-1) consists of all the information, input and derived, that defines the aircraft. The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. This information can be the result of the sizing task; can come entirely from input, for a fixed model; or can come from the sizing task in a previous case or previous job. The aircraft description information is available to all tasks and all solutions (indicated by light arrows). The sizing task determines the dimensions, power, and weight of a rotorcraft that can perform a specified set of design conditions and missions. The aircraft size is characterized by parameters such as design gross weight, weight empty, rotor radius, and engine power available. The relations between dimensions, power, and weight generally require an iterative solution. From the design flight conditions and missions, the task can determine the total engine power or the rotor radius (or both power and radius can be fixed), as well as the design gross weight, maximum takeoff weight, drive system torque limit, and fuel tank capacity. For each propulsion group, the engine power or the rotor radius can be sized. Missions are defined for the sizing task, and for the mission performance analysis. A mission consists of a number of mission segments, for which time, distance, and fuel burn are evaluated. For the sizing task, certain missions are designated to be used for design gross weight calculations; for transmission sizing; and for fuel tank sizing. The mission parameters include mission takeoff gross weight and useful load. For specified takeoff fuel weight with adjustable segments, the mission time or distance is adjusted so the fuel required for the mission (burned plus reserve) equals the takeoff fuel weight. The mission iteration is on fuel weight or energy. Flight conditions are specified for the sizing task, and for the flight performance analysis. For the sizing task, certain flight conditions are designated to be used for design gross weight calculations; for transmission sizing; for maximum takeoff weight calculations; and for antitorque or auxiliary thrust rotor sizing. The flight condition parameters include gross weight and useful load. For flight conditions and mission takeoff, the gross weight can be maximized, such that the power required equals the power available. A flight state is defined for each mission segment and each flight condition. The aircraft performance can be analyzed for the specified state, or a maximum effort performance can be identified. The maximum effort is specified in terms of a quantity such as best endurance or best range, and a variable such as speed, rate of climb, or altitude. The aircraft must be trimmed, by solving for the controls and motion that produce equilibrium in the specified flight state. Different trim solution definitions are required for various flight states. Evaluating the rotor hub forces may require solution of the blade flap equations of motion.

NDARC↗

NASA NTRS2023

NDARC - NASA Design and Analysis of Rotorcraft: Input - Appendix 3

The NDARC code performs design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance analysis, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. Figure 1-1 illustrates the tasks. The principal tasks (sizing, mission analysis, flight performance analysis) are shown in the figure as boxes with heavy borders. Heavy arrows show control of subordinate tasks. The aircraft description (figure 1-1) consists of all the information, input and derived, that defines the aircraft. The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. This information can be the result of the sizing task; can come entirely from input, for a fixed model; or can come from the sizing task in a previous case or previous job. The aircraft description information is available to all tasks and all solutions (indicated by light arrows). The sizing task determines the dimensions, power, and weight of a rotorcraft that can perform a specified set of design conditions and missions. The aircraft size is characterized by parameters such as design gross weight, weight empty, rotor radius, and engine power available. The relations between dimensions, power, and weight generally require an iterative solution. From the design flight conditions and missions, the task can determine the total engine power or the rotor radius (or both power and radius can be fixed), as well as the design gross weight, maximum takeoff weight, drive system torque limit, and fuel tank capacity. For each propulsion group, the engine power or the rotor radius can be sized. Missions are defined for the sizing task, and for the mission performance analysis. A mission consists of a number of mission segments, for which time, distance, and fuel burn are evaluated. For the sizing task, certain missions are designated to be used for design gross weight calculations; for transmission sizing; and for fuel tank sizing. The mission parameters include mission takeoff gross weight and useful load. For specified takeoff fuel weight with adjustable segments, the mission time or distance is adjusted so the fuel required for the mission (burned plus reserve) equals the takeoff fuel weight. The mission iteration is on fuel weight or energy. Flight conditions are specified for the sizing task, and for the flight performance analysis. For the sizing task, certain flight conditions are designated to be used for design gross weight calculations; for transmission sizing; for maximum takeoff weight calculations; and for antitorque or auxiliary thrust rotor sizing. The flight condition parameters include gross weight and useful load. For flight conditions and mission takeoff, the gross weight can be maximized, such that the power required equals the power available. A flight state is defined for each mission segment and each flight condition. The aircraft performance can be analyzed for the specified state, or a maximum effort performance can be identified. The maximum effort is specified in terms of a quantity such as best endurance or best range, and a variable such as speed, rate of climb, or altitude. The aircraft must be trimmed, by solving for the controls and motion that produce equilibrium in the specified flight state. Different trim solution definitions are required for various flight states. Evaluating the rotor hub forces may require solution of the blade flap equations of motion.

NDARC↗

NASA NTRS1999

Control of Meridional Flow in Circular Cylinders by a Travelling Axial Magnetic Field

Convective flow in a Bridgman or float zone configuration significantly affects the interface shape and segregation phenomena. While the primary causative factor for this flow is buoyancy induced convection in an enclosed Bridgman melt, the presence of a free surface gives rise to surface tension driven flows in the floating zone processing of melts. It is of interest to curtail these flows in order to realize near quiescent growth conditions that have shown to result in crystals with good longitudinal and radial homogeneity and thereby of better overall quality. While buoyancy effects can be reduced by careful processing in a low gravity (space) environment, the reduction of Marangoni flows due to surface tension variations is not that straight forward. Attempts have been made with some limited success with the use of external fields to affect the melt thermo-fluid behavior. The use of a static magnetic field that reduces convective contamination through the effects of a non-intrusively induced, dissipative Lorentz force in an electrically conducting melt is one such approach. Experiments have shown that axial fields of the order of 5 Tesla can significantly eliminate convection and yield close to diffusion limited crystal growth conditions. The generation and use of such high magnetic fields require substantial hardware and incur significant costs for its operation. Lately, the use of rotating magnetic fields has been tested in semiconductor crystal growth. The method is fairly well known and commonly used in metal processing but its adaptation to crystal growth of semiconductors is fairly recent. The elegance of the technique rests in its low power requirement (typically 10-20 milli-Tesla at 50-400 Hz) and its efficacy in curtailing deleterious temperature fluctuations in the melt. A rotating magnetic field imposes a rotational force and thereby induces a circulation within the melt that tends to dominate other sporadic convective effects. Thus a known low level of convective flow is introduced into the system. A new novel variation of the Lorentz force mechanism is proposed and investigated in this study. Since one of the desired process conditions in melt crystal growth is the minimization of convective effects, this investigation examines the use of an external field of magnetic origin to counteract existing convective flow within the melt. This is accomplished by utilizing a running or traveling axial magnetic wave in the system. The concept is similar to the use of vibrational means in order to induce streaming flows that oppose buoyant or surface tension driven convection in the system. The rotation direction as well as the magnitude (strength) of this circulation can be easily controlled by external inputs thus affording a direct means of controlling the developing shape of the crystallizing front (interface). The theoretical model of this technique is fully developed and presented in this paper. Results from the solution of the developed governing equations and boundary conditions are also presented. An experimental demonstration of the concept is presented through the suppression of natural convective flow in a mercury column. Implications to crystal growth systems will be fully explored in the final manuscript.

Mazuruk, K.↗

NASA NTRS1974

The static nonlinear analysis of shells of revolution (SNASOR II)

Utilizing stiffness matrices and supplying as input the loading and boundary conditions, program generates equilibrium equations for structure. Nonlinear strain energy terms result in pseudogeneralized forces which are combined with applied generalized forces. Resulting set of nonlinear algebraic equilibrium equations is solved by one of several methods.

Stricklin, J. A.↗

NASA NTRS1973

Hydrogen-oxygen auxiliary propulsion for the space shuttle. Volume 1: High pressure thrusters

Technology for long life, high performing, gaseous hydrogen-gaseous oxygen rocket engines suitable for auxiliary propulsion was provided by a combined analytical and experimental program. Propellant injectors, fast response valves, igniters, and regeneratively and film-cooled thrust chambers were tested over a wide range of operating conditions. Data generated include performance, combustion efficiency, thermal characteristics film cooling effectiveness, dynamic response in pulsing, and cycle life limitations.

Source record↗

NASA NTRS1974

Pioneer 9 plasma wave and solar plasma measurements for the August 1972 storm period

The solar disturbances of August 1972 produced large-scale solar wind perturbations that were detected by the Pioneer 9 plasma probe, electric field detector, and magnetometer for an extended time period commencing early on August 3. During this ten-day interval the interplanetary plasma parameters at r approximately equal 0.8 AU varied over unusually wide ranges, so that the conditions for generation of high and low VLF wave levels could be identified fairly readily. It is demonstrated that no measurable signals were detected in the broadband electric field channel (sensitive to waves with f greater than or equal to 100 Hz in the spacecraft frame of reference) unless the proton density was high enough to yield a proton plasma frequency with f greater than or about equal to 100 Hz. The analysis suggests that waves related to ion acoustic oscillations were detected throughout the extended storm period.

Scarf, F. L.↗

NASA NTRS1978

Global crop production forecasting - A simulation analysis of the data system problems and their solutions

Alternative data systems for a global crop production forecasting system were studied with the aid of a unique simulation facility called the Data System Dynamic Simulator (DSDS). Information system requirements were determined and compared with existing and planned data systems, and deficiencies were identified and analyzed. A first step was to determine the data load for an operational global crop production forecasting system as a function of data frequency, crop types, biophases, cloud coverage, and number of satellites. The DSDS was used to correlate the interrelated influence of orbital parameters, crop calendars, and cloud conditions to generate global data loading profiles. Some of the more important conclusions and the main features of the simulation system are presented.

Golden, H.↗

NASA NTRS1983

Peculiarities in formation of Arabidopsis Thaliana (L.) Heynh, generative organs under space flight conditions

Peculiarities in the formation of the andrecium and gynecium elements are described for Arabidopsis plants grown from the stages of two cotyledonous leaves in the Svitoblok-1 device on board the Salyut 6 orbital research station and in the laboratory. It is established that flower buds and flowers, normally formed in habitus, contain sterile elements of andrecium and gynecium whose degeneration occurs at different developmental stages of the Arabidopsis plants in the experiment under conditions of weightlessness.

Kordyum, Y. L.↗

NASA NTRS1983

Progress in computational physics

Recent progress in computational methods for time dependent fluid dynamics is presented. The emphasis is on advances applicable to large scale systems with the connection between the numerics and the physics of the code stressed. All aspects of a working code are discussed including such topics as initialization, boundary conditions, grid generation in addition to algorithmic advances. One sometimes uses a time dependent method as an iteration procedure to reach a steady state solution. Work in accelerating the convergence to the steady state is also surveyed.

Turkel, E.↗

NASA NTRS1983

HDM/PASCAL Verification System User's Manual

The HDM/Pascal verification system is a tool for proving the correctness of programs written in PASCAL and specified in the Hierarchical Development Methodology (HDM). This document assumes an understanding of PASCAL, HDM, program verification, and the STP system. The steps toward verification which this tool provides are parsing programs and specifications, checking the static semantics, and generating verification conditions. Some support functions are provided such as maintaining a data base, status management, and editing. The system runs under the TOPS-20 and TENEX operating systems and is written in INTERLISP. However, no knowledge is assumed of these operating systems or of INTERLISP. The system requires three executable files, HDMVCG, PARSE, and STP. Optionally, the editor EMACS should be on the system in order for the editor to work. The file HDMVCG is invoked to run the system. The files PARSE and STP are used as lower forks to perform the functions of parsing and proving.

Hare, D.↗

NASA NTRS1985

Numerical techniques for large cosmological N-body simulations

Techniques for carrying out large N-body simulations of the gravitational evolution of clustering in the fundamental cube of an infinite periodic universe are described and compared. The accuracy of the forces derived from several commonly used particle mesh schemes is examined, showing how submesh resolution can be achieved by including short-range forces between particles by direct summation techniques. The time integration of the equations of motion is discussed, and the accuracy of the codes for various choices of 'time' variable and time step is tested by considering energy conservation as well as by direct analysis of particle trajectories. Methods for generating initial particle positions and velocities corresponding to a growing mode representation of a specified power spectrum of linear density fluctuations are described. The effects of force resolution are studied and different simulation schemes are compared. An algorithm is implemented for generating initial conditions by varying the number of particles, the initial amplitude of density fluctuations, and the initial peculiar velocity field.

Efstathiou, G.↗