A comparison of conventional and tracking filter systems for launch vehicle stabilization
Adaptive tracking filter for bending mode stabilization of large flexible boosters
Cunningham, D. C.↗
SEARCH · Search NASA
Results for “conventional vehicles”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Microsimulation of Energy and Flow Effects from Optimal Automated Driving in Mixed Traffic
In this paper we study the energy and traffic impact of a proposed Anticipative Cruise Controller in a PTV VISSIM microsimulation environment. We dissect our controller into two parts: 1. the unconnected mode, active when following a human-driven vehicle, and 2. the connected mode, active when following another automated vehicle equipped with connectivity. Probabilistic constraints balance safety considerations with inter-vehicle compactness, and vehicle constraints for acceleration capabilities are expressed through the use of powertrain maps. Emergent highway traffic scenarios are then modeled using time headway distributions from empirical traffic data. To study the impact of automation over a range of demands of free-flow to stop-and-go, we vary vehicle flux from low to high and vary automated vehicle penetration from low to high. When examining all-human driving scenarios, network capacity failed to meet demand in high-volume scenarios, such as rush-hour traffic. We further find that with connected automated vehicles introduced, network capacity was improved to support the high-volume scenarios. Finally, we examine energy efficiencies of the fleet for conventional, electric, and hybrid vehicles. We find that automated vehicles perform at a 10%-20% higher energy efficiency over human drivers when considering conventional powertrains, and find that automated vehicles perform at a 3%-9% higher energy efficiency over human drivers when considering electric and hybrid powertrains. Due to secondary effects of smoothing traffic flow and reducing unnecessary braking, energy benefits also apply to human-driven vehicles that interact with automated ones. Such simulated humans were found to drive up to 10% more energy-efficiently than they did in the baseline all-human scenario.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
1983 LTA technology assessment
Several aspects of LTA (lighter-than-air) technology development are reviewed. Technological developments of classical airships through 1974 are examined. A brief historical and technological summary of five specialized LTA equipment concepts is presented: metal-clad airships, free balloons, semibuoyant vehicles, high-altitude platforms, and tethered aerostats. Current LTA technology developments are reviewed with particular emphasis on VTOL airships capable of heavy lift and on long endurance types for coastal maritime patrol. Finally, the future prospects of LTA system development are considered with attention given to manned conventional and hybrid vehicles, tethered vehicles, and RPVs.
Ashford, R. L.↗
Conventional and Bimodal Nuclear Thermal Rocket (NTR) Artificial Gravity Mars Transfer Vehicle Concepts
A variety of countermeasures have been developed to address the debilitating physiological effects of "zero-gravity" (0-g) experienced by cosmonauts and astronauts during their approximately 0.5-1.2 year long stays in LEO (Low Earth Orbit). Longer interplanetary flights, combined with possible prolonged stays in Mars orbit, could subject crewmembers to up to approximately 2.5 years of weightlessness. In view of known and recently diagnosed problems associated with 0-g, an artificial gravity spacecraft offers many advantages and may indeed be an enabling technology for human flights to Mars. A number of important human factors must be taken into account in selecting the rotation radius, rotation rate, and orientation of the habitation module or modules. These factors include the gravity gradient effect, radial and tangential Coriolis forces, along with cross-coupled acceleration effects. Artificial gravity (AG) Mars transfer vehicle (MTV) concepts are presented that utilize both conventional NTR, as well as, enhanced "bimodal" nuclear thermal rocket (BNTR) propulsion. The NTR is a proven technology that generates high thrust and has a specific impulse (I (sub sp)) capability of approximately 900 s - twice that of today's best chemical rockets. The AG/MTV concepts using conventional NTP carry twin cylindrical "ISS-type" habitation modules with their long axes oriented either perpendicular or parallel to the longitudinal spin axis of the MTV and utilize photovoltaic arrays (PVAs) for spacecraft power. The twin habitat modules are connected to a central operations hub located at the front of the MTV via two pressurized tunnels that provide the rotation radius for the habitat modules. For the BNTR AG/MTV option, each engine has its own "closed" secondary helium-xenon gas loop and Brayton rotating unit that can generate tens of kilowatts (kW (sub e)) of spacecraft electrical power during the mission coast phase eliminating the need for large PVAs. A single inflatable "TransHab-type" habitation module is also used with multiple vertical floors oriented radial to the MTV spin axis. The BNTR MTV's geometry - long and linear - is naturally compatible with AG operation. By rotating the vehicle about its center-of-mass and perpendicular to its flight vector at approximately 3.0 - 5.2 rpm, a centrifugal force and AG environment corresponding to approximately 0.38 - 1.0 g can be established to help maintain crew fitness out to Mars and back. Vehicles using NTP/BNTP can more readily accommodate the heavier payload mass and increased RCS propellant loading associated with AG operation, and can travel faster to and from Mars thereby reducing the crew's exposure to galactic cosmic radiation and solar flares. Mission scenario descriptions, key vehicle features and operational characteristics for each propulsion options are presented using the lift capability and payload volumes estimated for the SLS-1A and HLV.
Nuclear Propulsion↗
Conventional and Bimodal Nuclear Thermal Rocket (NTR) Artificial Gravity Mars Transfer Vehicle Concepts
A variety of countermeasures have been developed to address the debilitating physiological effects of zero-gravity (0-g) experienced by cosmonauts and astronauts during their approximately 0.5 to 1.2 year long stays in low Earth orbit (LEO). Longer interplanetary flights, combined with possible prolonged stays in Mars orbit, could subject crewmembers to up to approximately 2.5 years of weightlessness. In view of known and recently diagnosed problems associated with 0-g, an artificial gravity (AG) spacecraft offers many advantages and may indeed be an enabling technology for human flights to Mars. A number of important human factors must be taken into account in selecting the rotation radius, rotation rate, and orientation of the habitation module or modules. These factors include the gravity gradient effect, radial and tangential Coriolis forces, along with cross-coupled acceleration effects. Artificial gravity Mars transfer vehicle (MTV) concepts are presented that utilize both conventional NTR, as well as, enhanced bimodal nuclear thermal rocket (BNTR) propulsion. The NTR is a proven technology that generates high thrust and has a specific impulse (Isp) capability of approximately 900 s-twice that of today's best chemical rockets. The AG/MTV concepts using conventional Nuclear Thermal Propulsion (NTP) carry twin cylindrical International Space Station (ISS)- type habitation modules with their long axes oriented either perpendicular or parallel to the longitudinal spin axis of the MTV and utilize photovoltaic arrays (PVAs) for spacecraft power. The twin habitat modules are connected to a central operations hub located at the front of the MTV via two pressurized tunnels that provide the rotation radius for the habitat modules. For the BNTR AG/MTV option, each engine has its own closed secondary helium(He)-xenon (Xe) gas loop and Brayton Rotating Unit (BRU) that can generate 10s of kilowatts (kWe) of spacecraft electrical power during the mission coast phase eliminating the need for large PVAs. A single inflatable TransHab-type habitation module is also used with multiple vertical floors oriented radial to the MTV spin axis. The BNTR MTV's geometry-long and linear-is naturally compatible with AG operation. By rotating the vehicle about its center-of-mass (CM) and perpendicular to its flight vector at approximately 3.0 to 5.2 rpm, a centrifugal force and AG environment corresponding to approximately 0.38 to 1.0 g can be established to help maintain crew fitness out to Mars and back. Vehicles using NTP/ Bimodal Nuclear Thermal Propulsion (BNTP) can more readily accommodate the heavier payload mass and increased RCS propellant loading associated with AG operation, and can travel faster to and from Mars thereby reducing the crew's exposure to galactic cosmic radiation and solar flares. Mission scenario descriptions, key vehicle features and operational characteristics for each propulsion option are presented using the lift capability and payload volumes estimated for the Space Launch System (SLS)-1B and followon Heavy Lift Vehicle (HLV).
Nuclear Propulsion↗
Delivering Clean Air in Denver: Propane Trucks and Infrastructure in Mail Delivery Application
In 2021, Drive Clean Colorado, a Denver-based Clean Cities coalition, initiated the deployment of five Class 6 medium-duty propane autogas delivery trucks into a United States Postal Service (USPS) mail delivery contractor fleet with the goal of providing a proof-of-concept demonstration for mail delivery fleets nationwide. Funded by the U.S. Department of Energy's Office of Energy Efficiency & Renewable Energy, the project, titled "Delivering Clean Air in Denver: Propane Trucks and Infrastructure in Mail Delivery Application," enabled the purchase and deployment of the propane-powered trucks, refueling infrastructure, and supporting analysis by the National Renewable Energy Laboratory (NREL). Key objectives of the analysis included calculating the propane vehicles' emissions reductions, analyzing the costs and operational performance of the propane fleet compared to conventional diesel-powered vehicles, and evaluating the viability of propane as a clean and cost-effective alternative to conventional diesel trucks (AFDC 2023b, 2023c). The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a clean and cost-effective alternative to conventional diesel trucks. This proof-of-concept demonstration is expected to lead to improved understanding of the performance attributes, costs, and operational issues to inform technology adoption decisions, helping to spur market transformation toward lower-emission truck fleets. By reducing the risk of first adoption, potential exists to transform the U.S. Postal Service (USPS) mail delivery system into a lower-carbon national fleet. This technical report details the vehicle duty cycle characterization and fleet cost and performance comparison performed by the National Renewable Energy Laboratory, in addition to estimated emissions reductions for delivery operations.
33 ADVANCED PROPULSION SYSTEMS↗
Aerodynamic Design Opportunities for Future Supersonic Aircraft
A discussion of a diverse set of aerodynamic opportunities to improve the aerodynamic performance of future supersonic aircraft has been presented and discussed. These ideas are offered to the community in a hope that future supersonic vehicle development activities will not be hindered by past efforts. A number of nonlinear flow based drag reduction technologies are presented and discussed. The subject technologies are related to the areas of interference flows, vehicle concepts, vortex flows, wing design, advanced control effectors, and planform design. The authors also discussed the importance of improving the aerodynamic design environment to allow creativity and knowledge greater influence. A review of all of the data presented show that pressure drag reductions on the order of 50 to 60 counts are achievable, compared to a conventional supersonic cruise vehicle, with the application of several of the discussed technologies. These drag reductions would correlate to a 30 to 40% increase in cruise L/D (lift-to-drag ratio) for a commercial supersonic transport.
Wood, Richard M.↗
Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2020 Excel)
To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.
Wang, Michael↗
Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2021 Excel)
To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.
Wang, Michael↗
Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2022 Excel)
To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.
Wang, Michael↗
Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2023 Excel)
To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.
Wang, Michael↗
Machine learning models for maintenance cost estimation in delivery trucks using diesel and natural gas fuels
The maintenance costs can represent about 15%–60% of the cost of produced goods depending on the type of goods transported. To comply with stringent emissions regulations, diesel engines are incorporated with complex after-treatment systems that demand increased maintenance. The availability of alternative fuels such as natural gas and propane has fostered the natural gas and propane powertrain systems as well as electrification options for heavy- and medium-duty vehicles. A critical barrier to adopting alternative fuel vehicles has been the lack of knowledge on comparative vehicle maintenance/repair costs with conventional diesel. Moreover, the region of operation, the type of vehicle operation, and seasonal temperature changes also affect the duty cycle which impacts the maintenance and repair costs. This study focuses on estimating the cost-per-mile for heavy-duty vehicles using machine learning models such as random forest, xgboost, neural networks, and a super-learner model. The super-learner model achieved an error as low as 0.0068 $/mile for mean absolute error and 0.0086 $/mile for root mean square error with a coefficient of determination/R-Squared of 97.28%. Specifically, the paper investigates the data collected from the maintenance and repair costs associated with delivery trucks using diesel and natural gas fuels. Since the availability of data is the major constraint, we leveraged the data collected by West Virginia University and the partnership with fleet companies. This allows for additional information related to maintenance costs and fleet-specific maintenance practices of alternative fuel vehicles. This study promotes clean fuel technologies and enables fleet management companies to adopt alternative fuel vehicles in case of similar or lower cost of maintenance compared to diesel vehicles resulting in reduced emissions and total cost of ownership.
Katreddi, Sasanka↗
Flexible Wing Base Micro Aerial Vehicles: Assessment of Controllability of Micro Air Vehicles
In the last several years, we have developed unique types of micro air vehicles that utilize flexible structures and extensible covering materials. These MAVs can be operated with maximum dimensions as small as 6 inches and carry reasonable payloads, such as video cameras and transmitters. We recently demonstrated the potential of these vehicles by winning the Fourth International Micro Air Vehicle Competition, held at Ft. Huachucha, Arizona in May 2000. The pilots report that these vehicles have unusually smooth flying characteristics and are relatively easy to fly, both in the standard RC mode and "through the camera" when at greater distances. In comparison, they find that similar sized vehicles with more conventional rigid construction require much more input from the pilot just to maintain control. To make these subjective observations more quantitative, we have devised a system that can conveniently record a complete history of all the RC transmitter stick movements during a flight. Post-flight processing of the stick movement data allows for direct comparisons between different types of MAVs when flown by the same pilot, and also comparisons between pilots. Eventually, practical micro air vehicles will be autonomously controlled, but we feel that the smoothest flying and easiest to fly embodiments will also be the most successful in the long run. Comparisons between several types of micro air vehicles will be presented, along with interpretations of the data.
Jenkins, David A.↗
Pterodactyl: Guidance and Control of a Symmetric Deployable Entry Vehicle using an Aerodynamic Control System
The NASA-funded Pterodactyl project seeks to advance the state-of-the-art for varying entry vehicle types by developing unconventional guidance and control technologies for Deployable Entry Vehicles (DEVs) that can be applied to different entry vehicle configurations. Prior work by the authors [1–5] involved developing both traditional and novel integrated guidance and control solutions for a Pterodactyl Baseline Vehicle (PBV), a variant of an asymmetric DEV called the Lifting Nano ADEPT (LNA) [6]. In the prior studies, two different guidance schemes were designed and implemented for the PBV: (i) traditional bank angle guidance developed using the Fully Numerical Predictor-Corrector Entry Guidance (FNPEG) and (ii) novel angle of attack and sideslip (α - β) guidance developed using FNPEG with Uncoupled Range Control [4]. Using Linear Quadratic Regulator (LQR) optimal control methods with state-feedback integral control designs, these guidance trajectories were designed to be tracked using (i) a conventional propulsive entry vehicle control hardware architecture - reaction control systems (RCS) and (ii) novel non-propulsive entry vehicle control systems - aerodynamic flap control system (FCS) and moving mass control system (MMCS) [1]. The novel FCS and MMCS architectures were designed to track α - β guidance commands while the RCS was designed to track bank angle commands. It was discovered that the asymmetric DEV, the PBV, experienced a non-zero induced roll moment due to sideslip that the FCS and MMCS architectures had limited capability to trim out. These two architectures were designed to provide independent angle of attack and sideslip commands with limited consideration for roll moment generation to trim. As a result, for the PBV, the FCS and MMCS configurations as designed, were limited in providing the control authority needed to track an α - β guidance trajectory [1]. These results form the motivation for the work presented in this paper - utilizing an aerodynamic control system to track α - β guidance commands for a symmetric DEV with the expectation that a symmetric entry vehicle will have zero or significantly reduced roll moment due to sideslip that the FCS can handle when tracking an α - β guidance trajectory. To demonstrate the feasibility of a novel guidance and control architecture on a DEV, we utilize a symmetric DEV, the PBV-II, for (i) the novel α - β guidance development using FNPEG with Uncoupled Range Control and (ii) LQR control design using eight aerodynamic control surfaces. This paper demonstrates that the novel uncoupled α - β guidance tracking can be achieved using aerodynamic control surfaces on a symmetric deployable entry vehicle configuration.
Wendy A Okolo↗
RouteE: A Vehicle Energy Consumption Prediction Engine
The emergence of connected and automated vehicles and smart cities technologies create the opportunity for new mobility modes and routing decision tools, among many others. To achieve maximum mobility and minimum energy consumption, it is critical to understand the energy cost of decisions and optimize accordingly. The Route Energy prediction model (RouteE) enables accurate estimation of energy consumption for a variety of vehicle types over trips or sub-trips where detailed drive cycle data are unavailable. Applications include vehicle route selection, energy accounting and optimization in transportation simulation, and corridor energy analyses, among others. The software is a Python package that includes a variety of pre-trained models from the National Renewable Energy Laboratory (NREL). However, RouteE also enables users to train custom models using their own data sets, making it a robust and valuable tool for both fast calculations and rigorous, data-rich research efforts. The pre-trained RouteE models are established using NREL's Future Automotive Systems Technology Simulator paired with approximately 1 million miles of drive cycle data from the Transportation Secure Data Center, resulting in energy consumption behavior estimates over a representative sample of driving conditions for the United States. Validations have been performed using on-road fuel consumption data for conventional and electrified vehicle powertrains. Transferring the results of the on-road validation to a larger set of real-world origin-destination pairs, it is estimated that implementing the present methodology in a green-routing application would accurately select the route that consumes the least fuel 90% of the time. The novel machine learning techniques used in RouteE make it a flexible and robust tool for a variety of transportation applications.
47 OTHER INSTRUMENTATION↗
Life-cycle analysis of greenhouse gas emissions from hydrogen delivery: A cost-guided analysis
The cost of hydrogen delivery for transportation accounts for most of the current H 2 selling price; delivery also requires substantial amounts of energy. In this work, we developed harmonized techno-economic and life-cycle emissions models of current and future H 2 production and delivery pathways. Our techno-economic analysis of dispensed H 2 costs guided our selection of pathways for the life-cycle analysis. In this paper, we present the results of market expansion scenarios using existing capabilities (for example, those that use H 2 from steam methane reforming, chlor-alkali, and natural gas liquid cracker plants), as well as results for future electrolysis plants that use nuclear, solar, and hydroelectric power. Reductions in greenhouse gas emissions for fuel cell electric vehicles compared to conventional gasoline pathways vary from 40% reduction for fossil-derived H 2 to 20-fold for clean H 2 . Supplemental tables with greenhouse gas emissions data for each step in the H 2 pathways enable readers to evaluate additional scenarios.
08 HYDROGEN↗
RouteE-Powertrain [SWR-19-19]
RouteE-Powertrain is a tool for predicting energy usage over a set of road links. RouteE-Powertrain is a Python package that allows users to work with a set of pre-trained mesoscopic vehicle energy prediction models for a varity of vehicle types. Additionally, users can train their own models if "ground truth" energy consumption and driving data are available. RouteE-Powertrain models predict vehicle energy consumption over links in a road network, so the features considered for prediction often include traffic speeds, road grade, turns, etc. The typical user will utilize RouteE's catalog of pre-trained models. Currently, the catalog consists of light-duty vehicle models, including conventional gasoline, diesel, hybrid electric (HEV), and battery electric (BEV). These models can be applied to link-level driving data (in the form of pandas dataframes) to output energy consumption predictions. Users that wish to train new RouteE models can do so. The model training function of RouteE enables users to use their own drive-cycle data, powertrain modeling system, and road network data to train custom models. https://pypi.org/project/nrel.routee.powertrain/ pip install nrel.routee.powertrain
Holden, Jacob↗
EV Load Forecasting Guide: A Report by the Energy Systems Integration Group’s EV Load Forecasting Task Force
Forecasting electricity usage is a foundational planning activity for utilities, underpinning billions of dollars in grid investments that ensure system reliability. Historically, forecasting relied on trends in economic and population growth; however, transportation electrification presents a new and complex planning challenge. Unlike conventional loads, electric vehicle (EV) charging has relatively limited usage history. In addition, charging is driven by complex human behaviors, is mobile, and at the same time can concentrate geographically in ways that, without proper planning, can quickly overwhelm local distribution systems.
Giraldez, Julieta [Electric Power Engineers, Austi↗