A computational tool exists for determining the relationship between gears in a drivetrain, specifically tailored for scenarios involving an eighth-mile distance. This tool accepts inputs such as engine RPM, tire size, desired final speed, and gear ratios to calculate the theoretical optimal gear settings. It provides values such as expected top speed in each gear and theoretical ET at the end of the eighth-mile. For example, a user inputs engine RPM of 7000, tire diameter of 26 inches, and a desired final speed of 110 mph. The tool then processes these values alongside selected gear ratios to output the calculated ET.
Determining optimal gear ratios is crucial for maximizing performance in drag racing or other speed-related competitions. Using an appropriate gearset helps an engine remain within its optimal power band throughout the course. Historically, these calculations were performed manually using complex formulas and charts, a time-consuming and error-prone process. These tools streamline the process and allow competitors to refine their setup quickly and efficiently.
The use of a purpose-built computation tool enables racers to assess various combinations of gears and other components, providing an advantage through precise adjustments. The following sections will delve into the specific inputs required, how the calculations are performed, and the various factors that can impact the final results.
1. Engine RPM Input
Engine Revolutions Per Minute (RPM) serves as a fundamental input parameter for a gear ratio computation tool designed for eighth-mile runs. It represents the rotational speed of the engine’s crankshaft, directly influencing the vehicle’s speed potential at each gear stage. The accuracy of the RPM input is critical; a discrepancy, however minor, cascades through all subsequent calculations, leading to inaccurate estimations of top speed and elapsed time (ET). For instance, if the tool utilizes an incorrect maximum RPM value that is lower than the engine’s actual capability, it will prematurely estimate shift points and lower predicted terminal velocity. This, in turn, can cause a vehicle to underperform significantly on the track.
The maximum engine RPM value, or redline, is typically used for the computational processes. This is the upper limit beyond which the engine should not operate to prevent damage. However, it is often beneficial to conduct a dynamometer test to determine the engine’s optimal power band. This allows the input of a more realistic maximum RPM, aligning the calculation closer to the engine’s peak performance capabilities. Furthermore, the tool utilizes the entered RPM, alongside gear ratios and tire size, to calculate the vehicle’s theoretical speed in each gear. This forms the basis for determining optimal shift points that keep the engine within its most efficient operating range for acceleration. If engine RPM is too low, it gives more shifting points which is waste of time for driver.
In summary, accurate engine RPM input is paramount for the reliability of the predictions of tool. It sets the boundaries for the calculations of theoretical speed, optimal shift points, and ultimately, the estimated elapsed time for the eighth-mile run. Without accurate engine RPM data, the gear ratio computation tool’s value is severely diminished, rendering its predictive capabilities unreliable. A precise understanding of the engine’s operational characteristics and limits is essential for maximizing the potential of such computational aids.
2. Tire Size Measurement
Tire size measurement is a crucial input for effectively utilizing a gear ratio computation tool designed for eighth-mile performance optimization. It directly influences the accuracy of speed and distance calculations, thereby affecting the reliability of the tool’s predictions. An incorrect tire size value introduces errors that propagate through all subsequent calculations.
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Effective Rolling Diameter
The effective rolling diameter is the distance the tire covers in one complete revolution. This value, not the nominal tire diameter, is what should be used in the calculation tool. The tool utilizes this diameter to correlate engine RPM and gear ratios with the vehicle’s forward velocity. Any discrepancy in the effective rolling diameter will result in an incorrect calculation of vehicle speed at a given engine RPM. For example, if a vehicle is equipped with tires that have a smaller effective rolling diameter than what is entered into the tool, the actual speed will be lower than predicted.
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Tire Deflection Under Load
At high speeds, tires undergo deflection due to the centrifugal forces and weight transfer. This deflection reduces the effective rolling diameter of the tire, altering the vehicle’s gearing. Ignoring this effect will lead to an overestimation of the vehicle’s speed at the end of the eighth-mile. Advanced tools may incorporate a factor to account for this tire deflection, enhancing the precision of calculations. For example, a drag radial tire at launch will have significantly more deflection than at the end of the track, due to the shift in load.
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Impact on Gear Ratio Selection
The tire size directly impacts the selection of appropriate gear ratios. A larger tire size requires a numerically lower (taller) gear ratio to maintain the same final drive ratio and desired top speed. Conversely, a smaller tire size necessitates a numerically higher (shorter) gear ratio. Selecting gears without accurate tire size data can result in the engine not operating within its optimal power band, leading to diminished performance. The tire size alters final drive ratio, this can have a big affect on performance.
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Consistency for Accurate Results
Maintaining consistent tire pressure and type is essential for repeatable results. Variations in tire pressure can alter the effective rolling diameter, affecting the accuracy of the calculations. Similarly, switching between different tire compounds or constructions can change the amount of tire deflection, impacting the gearing and vehicle speed. Ensuring consistency in these factors is crucial for maximizing the effectiveness of a gear ratio computation tool.
In conclusion, tire size measurement is a critical component of the calculations performed by a gear ratio computation tool. The effective rolling diameter, accounting for tire deflection under load, directly influences the vehicle’s speed and, consequently, the selection of optimal gear ratios. Ignoring the impact of tire size can lead to inaccurate predictions and suboptimal performance on the eighth-mile track. Accurate tire parameters, consistently measured and applied, are essential for maximizing the tool’s predictive capabilities and achieving the desired performance outcomes.
3. Final Speed Target
The final speed target is a critical input parameter for a gear ratio computation tool used in eighth-mile performance optimization. This target represents the desired vehicle speed at the end of the eighth-mile distance and serves as a benchmark against which the tool calculates optimal gear ratios. It’s a goal derived from factors such as engine power, vehicle weight, aerodynamic drag, and desired performance metrics. The tool uses this target in conjunction with other parameters, such as engine RPM, tire size, and individual gear ratios, to determine the gearing configuration that enables the vehicle to achieve the target speed. Failure to accurately define the final speed target diminishes the tool’s ability to provide effective gear ratio recommendations.
For example, consider two vehicles, both targeting an eighth-mile run. One vehicle is light and has high horsepower, aiming for a final speed of 130 mph. The other is heavier and has less power, targeting 110 mph. The gear ratio computation tool would prescribe significantly different gearing for these two vehicles, even with identical engines, solely based on the variance in final speed target. In practical application, incorrectly estimating the final speed target can result in suboptimal gearing, leading to the engine operating outside its peak power band or failing to reach the desired speed within the eighth-mile distance. These two examples provide the important relationship with the target speed.
In conclusion, the final speed target is not merely a desired outcome but an essential input that dictates the gear ratio computation tool’s functionality. Its accuracy and appropriateness directly impact the tool’s ability to optimize gearing for maximum performance. Challenges in accurately predicting final speed, such as accounting for variable environmental conditions or unpredictable vehicle behavior, can limit the tool’s effectiveness, underscoring the need for careful estimation and data collection when setting the final speed target. The final speed is an important part of the calculator.
4. Gear Ratio Selection
Gear ratio selection constitutes a core component of any computational tool designed to optimize performance in an eighth-mile run. This selection process directly influences the vehicle’s acceleration and top speed. A gear ratio computation tool enables users to evaluate various combinations of gear ratios and their effects on vehicle dynamics, providing a means to determine the optimal arrangement for a specific application. The tool leverages inputs such as engine RPM, tire size, and target final speed, alongside potential gear ratios, to predict the vehicle’s performance. An incorrect gear ratio selection, even with accurate inputs, negates the benefits of using such a computational aid. For example, if a tool predicts a specific gear ratio will enable a vehicle to reach 110 mph at the end of the eighth-mile but the driver selects a different ratio, the predicted result will be inaccurate.
The interrelationship between gear ratio selection and the tool extends beyond simple performance prediction. These computation tools provide a means to assess the impact of various gear changes on the engine’s RPM range throughout the run. Maintaining the engine within its optimal power band is critical for maximizing acceleration. An unsuitable gear ratio could result in the engine operating below its peak torque, hindering acceleration, or exceeding its maximum RPM, potentially causing damage. Gear ratio selection involves optimizing not only the final drive ratio but also the individual gear ratios within the transmission. This iterative process is facilitated by tools that allow users to quickly simulate the effects of various gear combinations, identifying those that yield the most desirable results, by keeping engine in the sweet spot power band.
Gear ratio selection is, therefore, an integral process of the eighth-mile run planning facilitated by this calculator. The efficacy of such a tool hinges on accurate input data and the informed selection of gear ratios. Utilizing computational tools enhances the selection process by allowing performance prediction under different gearing configurations, however it is still important to select gear ratio by the correct method to have successful performance. The challenge lies in accurately assessing all influencing factors and inputting correct data for a successful performance.
5. Calculated ET Prediction
The calculated Elapsed Time (ET) prediction represents a primary output of a gear ratio computation tool designed for optimizing eighth-mile performance. This prediction estimates the time it will take for a vehicle to traverse the eighth-mile distance, given a specific set of input parameters and selected gear ratios. The validity of the calculated ET prediction directly correlates with the accuracy of the input parameters, including engine RPM, tire size, gear ratios, and other relevant factors. The tool uses these inputs to simulate the vehicle’s acceleration and speed over the eighth-mile, projecting the ET based on the calculated results. This prediction serves as a crucial indicator of the effectiveness of a specific gear ratio setup. For example, a racer uses a computation tool with an accurate ET prediction to determine optimal gear combinations to try on race day.
The connection between gear ratio selection and ET prediction is interdependent. A computational tool generates an ET prediction based on the selected gear ratios. Evaluating multiple gear ratio combinations through the tool is an iterative process; the calculated ET prediction provides the basis for refining the gear selection. If the initial ET prediction is not competitive, alternative gear ratios can be evaluated to identify a configuration that yields a lower (faster) ET. Conversely, if the tool predicts an exceedingly low ET, it may indicate that the selected gear ratios are not realistically achievable, potentially exceeding the engine’s capabilities or resulting in excessive wheelspin. As an example, a user might initially select a gear ratio that the calculator shows as being able to achieve a 6.0 second ET, but only if they run at a tire size that causes wheelspin. The user might use the computational tool to find gear ratios that will result in a slightly slower ET but are more realistic, such as a 6.2 ET at a less aggressive tire size.
In summary, the calculated ET prediction constitutes a pivotal component of a gear ratio computation tool. Its accuracy directly influences the ability to optimize gear selection for maximum performance in an eighth-mile run. Although this can be very informative, the tool does not account for all the variables. Real world outcomes will vary. The tool is still valuable, as it can provide a solid platform for starting a race.
6. Optimal Shift Points
Optimal shift points are intrinsically linked to the functionality of a gear ratio computation tool intended for eighth-mile racing. These points, defined as specific engine RPMs at which gear changes should occur, are calculated by the tool to maximize acceleration and minimize elapsed time. The accuracy of the predicted shift points hinges on the precision of input parameters, including engine power curves, gear ratios, tire size, and vehicle weight. A gear ratio computation tool leverages these inputs to simulate the vehicle’s acceleration profile and identify the optimal RPM at which shifting to the next gear will result in the greatest increase in forward momentum. For example, the tool may determine that for a specific engine, shifting to second gear at 6800 RPM, rather than 7000 RPM, results in a faster overall eighth-mile time by keeping the engine within its optimal torque range.
The interdependence between gear ratio selection and optimal shift point determination is significant. A tool’s suggested shift points will vary based on the selected gear ratios. Altering the gear ratios necessitates a recalculation of the optimal shift points to ensure that the engine remains within its peak power band throughout the eighth-mile run. Real-world drag racing teams use data logging systems to refine the shift points suggested by these tools. These systems record engine RPM, vehicle speed, and acceleration data during test runs, enabling teams to identify minor adjustments to the shift points that can improve performance. The shift point will differ with different gear ratio set. If set is too close, there may be too many shifting points, which is wasting shift time.
In conclusion, optimal shift points are a critical output of a gear ratio computation tool. Their accuracy significantly impacts the effectiveness of the chosen gear setup for an eighth-mile run. The computational tool provides key insights that allow users to make informed decisions for their race. Understanding the role of optimal shift points helps users to know the tool is working at the highest value for racers. The tool allows racers to find key insights for an optimum run, with its shift point data and gear selection.
7. Drivetrain Efficiency
Drivetrain efficiency significantly influences the accuracy of a gear ratio computation tool designed for eighth-mile racing. Drivetrain efficiency refers to the percentage of engine power that is actually transferred to the wheels, after accounting for losses due to friction and other factors within the drivetrain components. The gear ratio computation tool relies on engine power data to predict vehicle acceleration and top speed, and therefore estimate ET, but it is vital that the tool account for loss of power through the drivetrain. Without considering drivetrain efficiency, the tool will overestimate the amount of power available at the wheels, leading to inaccurate predictions of vehicle performance and, ultimately, an ineffective gear ratio selection. For example, if the tool does not accurately account for drivetrain losses and calculates that a vehicle will achieve 120 mph at the end of the eighth-mile, but drivetrain losses cause the actual speed to be 115 mph, the selection of gear ratios becomes compromised, and the vehicle will likely underperform. An accurate computation tool will factor in drivetrain loss. It would be most accurate to account for these factors in an individual way. Instead of that, most calculators will assume an overall efficiency loss for the total drivetrain, which will be slightly less accurate, but still helpful.
The degree of drivetrain efficiency varies based on multiple factors, including the type of transmission (automatic or manual), the condition of the drivetrain components, and the quality of lubrication. Automatic transmissions generally exhibit lower efficiency compared to manual transmissions due to hydraulic losses within the torque converter. Worn bearings, improperly aligned shafts, and inadequate lubrication all contribute to increased friction and reduced drivetrain efficiency. High-performance racing applications often employ specialized drivetrain components and lubricants designed to minimize losses and maximize power transfer. A computation tool should allow adjustment of the assumed drivetrain efficiency based on these variables. To provide a specific example, a vehicle equipped with a well-maintained manual transmission and high-quality synthetic lubricants may exhibit drivetrain efficiency of 90%, while a vehicle with a worn automatic transmission and conventional lubricants may only achieve 75% efficiency.
The interrelation between drivetrain efficiency and the tool’s input parameters presents both a challenge and an opportunity. Accurate estimation of drivetrain efficiency requires detailed knowledge of the vehicle’s specific components and operating conditions. However, incorporating this information into the computational tool enhances its predictive capabilities, enabling more effective gear ratio optimization. Despite the difficulty in obtaining precise drivetrain efficiency data, accounting for its approximate impact on power delivery is crucial for maximizing the tool’s usefulness and achieving competitive performance in eighth-mile racing.
8. Data Accuracy Crucial
The effectiveness of a gear ratio computation tool for eighth-mile racing is fundamentally contingent upon the accuracy of the input data. This tool relies on precise values for parameters such as engine RPM, tire size, gear ratios, and vehicle weight to simulate vehicle performance and predict elapsed time (ET). Inaccurate input data introduces errors into the calculations, leading to suboptimal gear ratio selections and diminished performance on the track. The relationship between data accuracy and the tool is therefore causal: the quality of the input data directly determines the reliability of the output and the potential for performance gains. For example, a user inputs an incorrect tire size into a gear ratio calculator. Even if all other factors are correctly input, there will be inaccurate output, which hurts vehicle performance. The more variables input incorrectly, the further off the tool will be.
Data accuracy is not merely a desirable attribute but an essential component of using this type of computation tool effectively. The tool’s predictions are only as reliable as the data it receives. This necessitates a commitment to accurate measurement and data collection. For engine RPM, this may involve dyno testing to establish precise power curves. For tire size, this requires accounting for dynamic rolling radius under load. For vehicle weight, it demands accurate scale measurements. Each element contributes to the overall precision of the tool’s calculations. It would be more accurate to measure and input all variables accurately, because inaccuracies can cause misleading information.
In conclusion, data accuracy is paramount for maximizing the benefits of a gear ratio computation tool. The tool’s ability to provide informed guidance on gear selection hinges on the quality of the data it receives. While these tools offer the potential to enhance performance, their effectiveness is ultimately limited by the accuracy and completeness of the input data. The greater the accuracy, the higher the tool’s usefulness. It is the responsibility of the end-user to collect, measure, and input this information as accurately as possible to find performance advantages for their race car.
9. Environmental Factors
Environmental factors exert a measurable influence on vehicle performance in eighth-mile racing, thereby impacting the accuracy and effectiveness of a gear ratio computation tool. Variations in air density, temperature, humidity, and track conditions affect engine power output, aerodynamic drag, and tire traction. These changes necessitate adjustments to the gear ratio setup, highlighting the interconnectedness between environmental considerations and computational tools.
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Air Density
Air density, determined by altitude, temperature, and humidity, directly affects engine power output. Denser air contains more oxygen, allowing the engine to combust more fuel and generate greater power. Conversely, less dense air reduces engine output. A gear ratio computation tool should ideally account for air density variations to provide accurate predictions. For instance, a vehicle running at sea level on a cool day will generate more power than the same vehicle running at a high altitude on a hot day, requiring different gear ratios to optimize performance. Ignoring these variations results in inaccurate calculations and suboptimal gear selections. A racer competing on two different days should account for different weather. On a day of lower air density, it may be prudent to add a more aggressive gear ratio than on a day where air density is higher.
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Temperature
Ambient temperature influences both engine performance and tire traction. Lower temperatures generally increase air density and improve engine power. However, extremely low temperatures can reduce tire traction, negating some of the benefits of increased power. Higher temperatures decrease air density but can also improve tire grip, depending on the track surface and tire compound. An effective tool should allow users to input temperature data to adjust calculations accordingly. A racetrack in Phoenix, Arizona, will have significantly different air and track temperatures on a summer day versus a winter day, and this temperature variance can affect gearing choices.
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Humidity
Humidity affects air density and can influence engine performance, particularly in turbocharged or supercharged engines. High humidity levels displace oxygen in the air, reducing combustion efficiency and power output. Conversely, low humidity can increase air density and improve engine performance. Additionally, humidity can affect track conditions, influencing tire traction. A refined tool would incorporate humidity as a variable in its calculations. High humidity levels will change the air/fuel mixture and can alter how engine torque is applied.
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Track Conditions
Track conditions encompass factors such as surface temperature, surface roughness, and the presence of any contaminants (e.g., oil, dirt). These conditions directly affect tire traction, which is critical for acceleration. A slick or uneven track surface reduces traction, requiring adjustments to gear ratios to minimize wheelspin. Conversely, a well-prepared track surface with high traction allows for more aggressive gear ratios. While directly inputting track conditions into a gear ratio computation tool is challenging, experienced racers often use their knowledge of track conditions to adjust their gear ratio selections. A newly paved or well-maintained track will allow for a more aggressive gear ratio.
In summary, environmental factors exert a measurable influence on vehicle performance, necessitating careful consideration when utilizing a gear ratio computation tool. While some tools offer limited capabilities for incorporating environmental variables, experienced racers often rely on their knowledge of these factors to fine-tune their gear selections. A truly comprehensive tool would integrate detailed environmental data to provide the most accurate and effective gear ratio recommendations, but even lacking that feature, understanding environmental factors is critical to racing success. The racer must consider all factors to have the most effective tune and win the race. The environmental factors must be considered with the gear ratio calculator.
Frequently Asked Questions
This section addresses common inquiries regarding the use of computation tools to determine optimal gear ratios for eighth-mile racing applications. The information presented aims to clarify key concepts and dispel potential misconceptions.
Question 1: What inputs are essential for an eighth-mile gear ratio computation tool?
The functionality of a gear ratio computation tool relies on accurate input data. Essential parameters include engine RPM (maximum and power band), tire size (effective rolling diameter), vehicle weight, target final speed, and individual gear ratios within the transmission and final drive. The precision of these inputs directly influences the accuracy of the tool’s predictions.
Question 2: How does tire size affect gear ratio calculations?
Tire size, specifically the effective rolling diameter, directly impacts the relationship between engine RPM and vehicle speed. An incorrect tire size value will skew speed calculations, leading to inaccurate gear ratio recommendations. The tool accounts for this relationship to select ratios that enable the vehicle to reach the target speed within the eighth-mile distance.
Question 3: What is the significance of the final speed target?
The final speed target represents the desired vehicle speed at the end of the eighth-mile. This target serves as a benchmark against which the tool calculates optimal gear ratios. It reflects the vehicle’s power, weight, aerodynamic characteristics, and desired performance. The tool uses it to determine the gearing that enables the vehicle to achieve the desired speed.
Question 4: How does a gear ratio computation tool determine optimal shift points?
The gear ratio computation tool calculates shift points to maximize acceleration within the eighth-mile. These points represent the engine RPM at which gear changes should occur to maintain the engine within its optimal power band. This tool uses data regarding engine power, gear ratios, tire size, and vehicle weight to simulate the vehicles acceleration and pinpoint the RPM at which shifting is the best course of action.
Question 5: Why is drivetrain efficiency a critical consideration?
Drivetrain efficiency accounts for power losses within the drivetrain components. If the amount of power is not being fully used, it can influence calculations and estimations. This should be factored in or the calculations would be incorrect.
Question 6: What limitations exist regarding the accuracy of an eighth-mile gear ratio calculation tool?
Limitations stem from the tool’s reliance on accurate input data and its inability to fully account for real-world variables. Factors such as unpredictable weather, variations in track conditions, and tire slip can affect performance. The tool can only generate reliable predictions if input data is accurate.
Eighth-mile gear ratio calculations are an important part of winning. The gear ration calculator can make or break the vehicle performance.
Following sections will present further analysis regarding gear calculation.
Eighth-Mile Gear Ratio Optimization
The following tips are critical for accurately employing a computation tool for determining optimal gear ratios in eighth-mile racing. These strategies enhance the tool’s effectiveness, allowing for better performance optimization.
Tip 1: Validate Engine Power Data: Before utilizing a computation tool, verify engine power output using a dynamometer. This data, encompassing horsepower and torque across the RPM range, serves as the foundation for all subsequent calculations. Inaccurate data undermines the reliability of the tool’s recommendations.
Tip 2: Account for Tire Expansion: Under high-speed conditions, tire diameter increases due to centrifugal force. Factor this expansion into the tire size input. Ignoring tire expansion leads to an overestimation of vehicle speed and potentially incorrect gear selections.
Tip 3: Refine Final Speed Target: Establish a realistic final speed target based on prior track data and vehicle capabilities. A target that is either too high or too low will compromise the tool’s effectiveness in identifying the optimal gear ratios.
Tip 4: Optimize Shift Points Incrementally: Refine shift points through iterative adjustments. A computation tool provides a starting point, but real-world conditions often necessitate fine-tuning to maximize acceleration. Monitor engine RPM and vehicle speed during test runs to identify areas for improvement.
Tip 5: Assess Drivetrain Losses: Quantify drivetrain losses, as these affect the tool’s calculations. Lower losses mean higher efficiency and higher outputs. Improper data inputs create issues.
Tip 6: Account for Environmental Variance: Environmental conditions, notably air density, significantly affect engine performance. Adjust the tool’s inputs to account for changes in altitude, temperature, and humidity. This ensures the gear ratio selection remains optimal under varying conditions.
The points highlighted provide guidance for effectively utilizing a computation tool for gear ratio optimization in eighth-mile racing. Consistent application of these principles will improve the accuracy of the tool’s predictions and maximize vehicle performance. This understanding is critical for leveraging the tool to its full potential.
The following sections conclude this discussion, summarizing key takeaways and offering directions for continued learning and application.
Conclusion
The preceding analysis has delineated the function and application of a computational aid used for determining optimal gear ratios in eighth-mile racing contexts. The efficacy of this tool is contingent upon the precision of input parameters, including engine RPM, tire dimensions, desired final velocity, and the gear ratios themselves. A comprehensive understanding of drivetrain mechanics, coupled with accurate data, is essential for the effective employment of such tools. Real-world testing and analysis remain critical components in the process of refining gear selections.
The pursuit of optimized gearing represents a continuing endeavor within competitive motorsports. As technology advances, computational tools will likely become more sophisticated, integrating real-time data and advanced algorithms to further refine gear ratio selection. Nevertheless, the underlying principles of physics and engineering will persist, necessitating a thorough understanding of these factors for maximizing performance on the track. The proper employment of computational tools, alongside experienced judgment, provides a clear path toward achieving success in eighth-mile racing.
