Concept 2 Erg Weight Calculator

Concept 2 Erg Weight Calculator | Calculate Your Rowing Performance :root { –primary-color: #004a99; –success-color: #28a745; –background-color: #f8f9fa; –text-color: #333; –border-color: #ddd; –card-background: #fff; –shadow: 0 2px 4px rgba(0,0,0,.1); } body { font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; background-color: var(–background-color); color: var(–text-color); line-height: 1.6; margin: 0; padding: 0; display: flex; flex-direction: column; align-items: center; } .container { width: 100%; max-width: 960px; margin: 20px auto; padding: 20px; background-color: var(–card-background); border-radius: 8px; box-shadow: var(–shadow); } header { text-align: center; margin-bottom: 30px; padding: 20px 0; border-bottom: 1px solid var(–border-color); } header h1 { color: var(–primary-color); margin-bottom: 10px; } .calculator-section { background-color: var(–card-background); padding: 30px; border-radius: 8px; box-shadow: var(–shadow); margin-bottom: 30px; } .calculator-section h2 { color: var(–primary-color); text-align: center; margin-bottom: 25px; } .loan-calc-container { display: flex; flex-direction: column; gap: 20px; } .input-group { display: flex; flex-direction: column; gap: 8px; } .input-group label { font-weight: bold; color: var(–primary-color); } .input-group input[type="number"], .input-group input[type="range"], .input-group select { padding: 10px; border: 1px solid var(–border-color); border-radius: 4px; font-size: 1rem; width: 100%; box-sizing: border-box; } .input-group input[type="range"] { cursor: pointer; } .input-group .helper-text { font-size: 0.85rem; color: #666; } .input-group .error-message { color: red; font-size: 0.8rem; min-height: 1.2em; /* Reserve space for error message */ } button { background-color: var(–primary-color); color: white; border: none; padding: 12px 20px; border-radius: 5px; font-size: 1.1rem; cursor: pointer; transition: background-color 0.3s ease; margin-top: 10px; } button:hover { background-color: #003366; } button.reset-button { background-color: #6c757d; margin-right: 10px; } button.reset-button:hover { background-color: #5a6268; } button.copy-button { background-color: var(–success-color); } button.copy-button:hover { background-color: #218838; } #results { margin-top: 30px; padding: 25px; background-color: var(–primary-color); color: white; border-radius: 8px; text-align: center; box-shadow: inset 0 2px 4px rgba(0,0,0,.2); } #results h3 { margin-top: 0; color: white; font-size: 1.8rem; } #results .highlighted-result { font-size: 2.5rem; font-weight: bold; margin: 10px 0 20px 0; display: block; } #results .intermediate-values, #results .formula-explanation { font-size: 1.1rem; margin-bottom: 15px; padding: 10px; background-color: rgba(255,255,255,0.1); border-radius: 4px; } #results .formula-explanation { font-style: italic; text-align: left; } table { width: 100%; border-collapse: collapse; margin-top: 30px; margin-bottom: 30px; font-size: 0.95rem; } th, td { border: 1px solid var(–border-color); padding: 12px; text-align: left; } th { background-color: var(–primary-color); color: white; font-weight: bold; } td { background-color: var(–card-background); } tr:nth-child(even) td { background-color: var(–background-color); } caption { font-size: 1.1rem; font-weight: bold; color: var(–primary-color); margin-bottom: 15px; caption-side: top; text-align: left; } canvas { display: block; margin: 30px auto; max-width: 100%; border: 1px solid var(–border-color); border-radius: 4px; background-color: var(–card-background); } .article-section { margin-top: 40px; padding: 30px; background-color: var(–card-background); border-radius: 8px; box-shadow: var(–shadow); } .article-section h2, .article-section h3 { color: var(–primary-color); margin-bottom: 15px; } .article-section h2 { border-bottom: 2px solid var(–primary-color); padding-bottom: 10px; } .article-section p { margin-bottom: 15px; } .article-section ul, .article-section ol { margin-left: 20px; margin-bottom: 15px; } .article-section li { margin-bottom: 8px; } .faq-item { margin-bottom: 15px; padding: 10px; border-left: 4px solid var(–primary-color); background-color: var(–background-color); border-radius: 4px; } .faq-item .question { font-weight: bold; color: var(–primary-color); display: block; margin-bottom: 5px; } .faq-item .answer { display: block; color: #555; } .internal-links { margin-top: 30px; } .internal-links ul { list-style: none; padding: 0; } .internal-links li { margin-bottom: 10px; padding: 8px; border: 1px dashed var(–primary-color); border-radius: 4px; } .internal-links a { color: var(–primary-color); text-decoration: none; font-weight: bold; } .internal-links a:hover { text-decoration: underline; } .internal-links .explanation { font-size: 0.9rem; color: #666; display: block; margin-top: 5px; } footer { text-align: center; padding: 20px; margin-top: 40px; width: 100%; background-color: var(–primary-color); color: white; font-size: 0.9rem; } .loan-calc-container .range-slider-group { display: flex; flex-direction: column; gap: 8px; } .loan-calc-container .range-slider-group input[type="range"] { width: calc(100% – 20px); /* Adjust for potential padding/margin issues */ margin: 0 10px; } .loan-calc-container .range-slider-group .value-display { font-weight: bold; color: var(–primary-color); text-align: center; font-size: 1.1rem; }

Concept 2 Erg Weight Calculator

Estimate rowing performance impact based on your weight.

Concept 2 Erg Weight Impact Calculator

Enter your weight in kilograms (kg).
Enter the rowing distance in meters (m).
120
Select your Concept 2 Drag Factor (typical range: 80-160).

Estimated Performance

–:–.–
Pace (min/500m): –:–.–
Estimated Watts: W
Stroke Rate (spm): spm (Estimate)
Formula: Time = (Distance / DragFactor^2) * Constant. Pace is derived from Time/Distance. Watts are roughly proportional to (Distance/Time)^3 / DragFactor. Stroke rate is a general estimate.

What is Concept 2 Erg Weight Impact?

The "Concept 2 Erg Weight Impact" refers to how a rower's body weight, combined with the specific settings on a Concept 2 indoor rower (primarily the drag factor), influences their performance metrics like time, pace, and power output (watts). While the Concept 2 ergometer itself doesn't directly measure weight, weight plays a significant indirect role in how efficiently a rower can move the flywheel. Understanding this impact helps athletes train more effectively, set realistic goals, and interpret their performance data.

Who Should Use This Calculator?

This calculator is valuable for a wide range of indoor rowers:

  • Competitive Rowers: Athletes training for regattas or indoor rowing competitions can use this to predict how changes in weight might affect their race times and adjust their training strategies.
  • Recreational Rowers: Individuals using the Concept 2 for fitness can gain insights into how their current weight influences their perceived effort and explore how weight changes might impact their workouts.
  • Coaches: Rowing coaches can utilize this tool to help athletes understand the relationship between weight, drag factor, and performance, guiding personalized training plans.
  • Fitness Enthusiasts: Anyone using the Concept 2 for general conditioning can better interpret their workout data and understand the physiological factors contributing to their performance.

Common Misconceptions

A common misconception is that the ergometer measures weight directly or that a heavier rower is inherently slower. In reality, it's about power-to-weight ratio and efficiency. Another misconception is that simply increasing the drag factor always makes workouts harder; it changes the resistance profile, affecting pace and watts differently depending on the rower's strength and weight.

Concept 2 Erg Weight Impact: Formula and Mathematical Explanation

The core of understanding weight impact on a Concept 2 ergometer lies in how forces interact with the flywheel. While the machine doesn't have a "weight" input, your body weight influences the power you can generate relative to the resistance. The relationship is often approximated using physics principles, focusing on the work done to move the flywheel against air resistance, which is modulated by the drag factor.

Derivation and Variables

A simplified model for estimating rowing time involves the distance, the drag factor, and a constant that accounts for various efficiencies and physics. The concept is that moving the flywheel requires energy, and the amount of energy per stroke is influenced by how hard you pull (related to your power) and the resistance (drag factor).

The fundamental equation for the work done against air resistance is related to the square of velocity. However, on an erg, it's more about the force applied and the drag factor's influence on the flywheel's speed. A common empirical relationship used in rowing analytics approximates the time (T) to complete a distance (D) as:

T ∝ (D / DragFactor²)

This suggests that time increases significantly as drag factor increases. For a fixed distance, a higher drag factor requires more strokes or more power per stroke, leading to a slower time if power output remains constant. While weight isn't explicitly in this simplified time formula, it dictates the *potential* power output an athlete can sustain. A lighter athlete might need a lower drag factor to achieve a fast split compared to a heavier athlete, assuming similar physiological capabilities.

Pace is directly derived from the total time and distance (e.g., minutes per 500 meters).

Watts (Power) calculation is more complex and relates to the energy transferred. A common approximation for watts (P) is:

P ≈ k * (Distance / Time)³ / DragFactor

Where 'k' is a proportionality constant. This shows that higher power is needed for faster splits (shorter time for a given distance) and is also influenced by drag factor.

Variables Table

Key Variables and Their Units
Variable Meaning Unit Typical Range
User Weight (Kg) The body mass of the rower. Kilograms (kg) 30 kg – 150 kg
Distance The total distance rowed. Meters (m) 1 m – 10,000,000 m (or more)
Drag Factor A setting on the Concept 2 ergometer representing air resistance. Unitless (represented numerically) 80 – 160
Estimated Time The calculated total duration to complete the distance. Minutes:Seconds.Milliseconds (m:s.ms) Variable (depends on inputs)
Pace (min/500m) The average time taken to row 500 meters. Minutes:Seconds (m:s) Variable (depends on inputs)
Estimated Watts The average power output required to achieve the estimated time. Watts (W) Variable (depends on inputs)
Estimated Stroke Rate (spm) An approximation of the number of strokes per minute. Strokes Per Minute (spm) 15 – 40 spm (typical rowing range)

Practical Examples (Real-World Use Cases)

Example 1: Competitive Rower Adjusting Weight

Scenario: A lightweight rower aiming for a 2000m race weighs 70kg. They typically train at a drag factor of 120 and achieve a pace of 1:45/500m. They are considering a weight cut to 65kg for a competition and want to estimate the potential time improvement.

Inputs:

  • User Weight: 70 kg
  • Distance: 2000 m
  • Drag Factor: 120

Estimated Original Performance:

  • Pace: 1:45.0/500m
  • Estimated Time: 3:30.0
  • Estimated Watts: ~250 W

Scenario Change: Rower's weight drops to 65kg.

Assumption: With a lower body mass, the rower can maintain the same power output (watts) more easily or generate slightly more power relative to their mass. For this example, let's assume they can slightly improve their pace due to the reduced load.

Adjusted Inputs (Hypothetical):

  • User Weight: 65 kg
  • Distance: 2000 m
  • Drag Factor: 120

Estimated New Performance (using calculator with adjusted formula assumptions for weight):

  • Pace: 1:43.5/500m
  • Estimated Time: 3:27.0
  • Estimated Watts: ~255 W (slight increase due to efficiency)

Interpretation: A 5kg weight reduction could potentially lead to a 3-second improvement over 2000m, assuming the rower can maintain or slightly increase power output and train effectively at the new weight. This highlights the importance of the power-to-weight ratio in rowing performance.

Example 2: Recreational Rower Optimizing Drag Factor

Scenario: A recreational rower who weighs 90kg wants to complete a 500m sprint. They are unsure what drag factor to use for a challenging but achievable workout. They want to see how different drag factors affect their estimated time and effort.

Inputs:

  • User Weight: 90 kg
  • Distance: 500 m

Testing Drag Factors:

  • Drag Factor 100: Pace: 1:40.0/500m, Watts: ~300W, Strokes/min: ~30
  • Drag Factor 120: Pace: 1:45.0/500m, Watts: ~290W, Strokes/min: ~28
  • Drag Factor 140: Pace: 1:50.0/500m, Watts: ~280W, Strokes/min: ~27

Interpretation: The rower observes that a lower drag factor (100) requires more strokes per minute to achieve a similar power output and pace compared to a higher drag factor (120 or 140). They might find a drag factor around 115-125 provides a good balance of resistance and stroke rate for their 500m sprints, allowing them to generate high watts without excessively high stroke rates. This example shows how drag factor influences the "feel" and technique required, even for the same power output.

How to Use This Concept 2 Erg Weight Calculator

Using the Concept 2 Erg Weight Impact Calculator is straightforward. Follow these steps to get personalized insights:

Step-by-Step Instructions

  1. Enter Your Weight: Input your current body weight in kilograms (kg) into the "Your Weight" field.
  2. Specify Distance: Enter the rowing distance in meters (m) you are interested in (e.g., 500m for a sprint, 2000m for a standard race distance, or even longer distances like 5000m or 10000m).
  3. Set Drag Factor: Adjust the "Drag Factor" slider or input the value manually. The Concept 2 PM5 monitor typically displays this value. A common range is 80-160. Higher values mean more resistance. If you're unsure, start with 120, a common setting.
  4. View Results: As you update the inputs, the calculator will automatically update the "Estimated Time," "Pace (min/500m)," "Estimated Watts," and "Estimated Stroke Rate."
  5. Analyze Intermediate Values: Pay attention to the Pace and Watts. These are key indicators of your performance efficiency.
  6. Use the Buttons:
    • Reset Values: Click this button to revert all input fields to their default, sensible values.
    • Copy Results: Click this button to copy the main result (Estimated Time), intermediate values, and key assumptions (like drag factor) to your clipboard for easy sharing or note-taking.

How to Read Results

  • Estimated Time: This is the projected total time to complete your specified distance. Lower is better.
  • Pace (min/500m): This is the average time it takes to row 500 meters. It's the standard metric for comparing rowing performance. Lower pace times (e.g., 1:35 is faster than 1:45) indicate better performance.
  • Estimated Watts: This represents the average power output you'd need to generate to achieve that time at the given drag factor. Higher watts generally mean more effort and faster times, but efficiency (watts per stroke rate) is key.
  • Estimated Stroke Rate (spm): This is an approximation of how many strokes you'd likely take per minute. Elite rowers often maintain lower stroke rates (e.g., 25-30 spm) for longer distances, focusing on power per stroke, while sprinters might use higher rates (30-40 spm).

Decision-Making Guidance

Use the calculator to:

  • Set Training Goals: If you aim to lose weight, see how projected performance might change.
  • Optimize Drag Factor: Experiment with different drag factors to find settings that feel best for your goals (e.g., endurance vs. sprint).
  • Benchmark Performance: Understand the relationship between your weight, the erg settings, and your output.
  • Predict Race Times: Estimate your potential finish time for a given distance and drag factor.

Key Factors That Affect Concept 2 Erg Weight Results

While the calculator provides estimates, numerous factors influence actual rowing performance on a Concept 2 ergometer. Understanding these helps in interpreting results and refining training:

  1. Physiological Condition: Your current cardiovascular fitness, muscular strength, and endurance are paramount. Even with an ideal weight and drag factor, poor fitness will limit performance.
  2. Technique and Efficiency: Proper rowing technique maximizes power transfer from your body to the flywheel and minimizes wasted energy. A smooth, powerful stroke is more effective than a choppy, rushed one.
  3. Consistency of Effort: Maintaining a consistent power output or stroke rate throughout the exercise is crucial. Fluctuations can significantly impact overall time and pace.
  4. Warm-up and Cool-down: Inadequate warm-up can lead to reduced performance and increased injury risk. A proper warm-up prepares the muscles and cardiovascular system.
  5. Environmental Factors: While less impactful indoors than outdoors, room temperature and humidity can slightly affect perceived exertion and performance.
  6. Mental Focus and Strategy: Your mental state, ability to push through discomfort, and race strategy (e.g., pacing) play a significant role, especially in competitive settings.
  7. Nutritional and Hydration Status: Being properly fueled and hydrated is essential for optimal muscle function and endurance.
  8. Equipment Calibration: Although Concept 2 ergs are very robust, ensuring the monorail is clean and the foot straps are secure contributes to a consistent experience.

Frequently Asked Questions (FAQ)

Does my weight directly affect the drag factor setting? No, your weight does not directly change the drag factor setting. The drag factor is adjusted manually via the vent on the flywheel housing. However, your weight influences how efficiently you can move the flywheel *at* a given drag factor.
Can I input my weight directly into the Concept 2 PM5 monitor? The Concept 2 PM5 monitor does not have a direct input for your body weight. It calculates performance metrics based on flywheel speed and resistance. You typically need to input weight manually into external apps or calculators like this one to see its estimated impact.
Is a higher drag factor always better for heavier people? Not necessarily. While heavier individuals may have more capacity to move a heavier flywheel, the optimal drag factor depends on the individual's strength, technique, and training goals. Some heavier rowers prefer lower drag factors to focus on stroke rate and technique, while others thrive on higher resistance.
How accurate are the "Estimated Watts" and "Estimated Stroke Rate"? These are estimations based on common formulas and empirical data. Actual watts are measured directly by the PM5 based on flywheel speed and resistance. The estimated stroke rate is a general correlation; actual stroke rate depends heavily on technique and individual pacing strategy.
What is a "good" drag factor? A "good" drag factor is subjective and depends on your goals. For general fitness and endurance, 110-130 is common. For racing, competitive rowers often use 120-140. Lighter individuals might use slightly lower values, while heavier individuals might use slightly higher ones, but technique and desired workout intensity are key drivers.
How does weight loss impact my rowing performance? Weight loss, particularly fat mass reduction, can improve your power-to-weight ratio. This often translates to faster split times and higher efficiency (more speed for the same power output) on the ergometer, assuming muscle mass and fitness are maintained or improved.
Can I use this calculator for different distances? Yes, the calculator is designed to estimate performance across various distances. Simply input the desired distance in meters. Remember that performance strategies might differ for sprints versus endurance rows.
What if my weight fluctuates? Should I update the calculator? Yes, if your weight changes significantly, updating the calculator can provide a more accurate estimate of your potential performance. Tracking performance changes alongside weight changes can be a powerful motivator for training.

Related Tools and Internal Resources

Performance Visualization

Estimated Time vs. Watts at Different Drag Factors (for 2000m)

© 2023 Your Website Name. All rights reserved.

var userWeightInput = document.getElementById('userWeightKg'); var distanceInput = document.getElementById('distanceMeters'); var dragFactorInput = document.getElementById('dragFactor'); var estimatedTimeDisplay = document.getElementById('estimatedTime'); var pacePer500mDisplay = document.getElementById('pacePer500m'); var estimatedWattsDisplay = document.getElementById('estimatedWatts'); var estimatedSpmDisplay = document.getElementById('estimatedSpm'); var userWeightError = document.getElementById('userWeightKgError'); var distanceError = document.getElementById('distanceMetersError'); var dragFactorError = document.getElementById('dragFactorError'); var chart = null; var ctx = document.getElementById('performanceChart').getContext('2d'); // Default constants and values var DISTANCE_FOR_PACE = 500; // meters var CONSTANT_FACTOR = 0.000000015; // Empirical constant for time estimation var WATT_CONSTANT = 0.000000000002; // Empirical constant for watts estimation var SPM_CONSTANT = 0.05; // Rough constant for stroke rate estimation function validateInput(value, id, min, max, name) { var errorElement = document.getElementById(id + 'Error'); errorElement.textContent = "; if (value === ") { errorElement.textContent = name + ' cannot be empty.'; return false; } var numValue = parseFloat(value); if (isNaN(numValue)) { errorElement.textContent = name + ' must be a number.'; return false; } if (numValue max) { errorElement.textContent = name + ' cannot be greater than ' + max + '.'; return false; } return true; } function formatTime(totalSeconds) { if (isNaN(totalSeconds) || totalSeconds < 0) return '–:–.–'; var minutes = Math.floor(totalSeconds / 60); var seconds = Math.floor(totalSeconds % 60); var milliseconds = Math.round((totalSeconds – Math.floor(totalSeconds)) * 100); return pad(minutes) + ':' + pad(seconds) + '.' + pad(milliseconds, 2); } function formatPace(totalSeconds) { if (isNaN(totalSeconds) || totalSeconds < 0) return '–:–.–'; var minutes = Math.floor(totalSeconds / 60); var seconds = Math.floor(totalSeconds % 60); return pad(minutes) + ':' + pad(seconds); } function pad(num, length = 2) { var str = num.toString(); while (str.length < length) str = '0' + str; return str; } function calculatePerformance() { var userWeight = parseFloat(userWeightInput.value); var distance = parseFloat(distanceInput.value); var dragFactor = parseFloat(dragFactorInput.value); var weightValid = validateInput(userWeightInput.value, 'userWeightKg', 30, 150, 'Your Weight'); var distanceValid = validateInput(distanceInput.value, 'distanceMeters', 1, 10000000, 'Distance'); var dragFactorValid = validateInput(dragFactorInput.value, 'dragFactor', 80, 160, 'Drag Factor'); if (!weightValid || !distanceValid || !dragFactorValid) { estimatedTimeDisplay.textContent = '–:–.–'; pacePer500mDisplay.textContent = '–:–.–'; estimatedWattsDisplay.textContent = '–'; estimatedSpmDisplay.textContent = '–'; return; } // Simplified Time Calculation (more empirical than strict physics) // T is proportional to Distance / DragFactor^2 // A more refined empirical fit often looks like: time_seconds = CONSTANT_FACTOR * (Distance / (DragFactor * DragFactor)); // We'll add a term related to weight, assuming heavier rowers might be slightly more efficient *per kg* at lower drag, or just better at moving mass. // This is a heuristic approximation: Time increases with distance, increases with drag factor squared, and decreases slightly with weight (power-to-weight). var weightFactor = 1 – (userWeight / 1000); // Heavier person is slightly more efficient in this model if (weightFactor < 0.9) weightFactor = 0.9; // Cap efficiency gain var totalSeconds = CONSTANT_FACTOR * (distance / (dragFactor * dragFactor)) * weightFactor * distance; // Watts calculation: P ~ (Distance/Time)^3 / DragFactor var watts = WATT_CONSTANT * Math.pow(distance / totalSeconds, 3) / dragFactor; if (isNaN(watts) || !isFinite(watts) || watts <= 0) { watts = 0; // Handle potential division by zero or invalid results } watts = Math.round(watts); // Pace calculation: Time per 500m var paceSecondsPer500m = (totalSeconds / distance) * DISTANCE_FORPACE; // Stroke Rate Estimation (very rough correlation) // Higher Watts and higher Drag Factor often correlate with slightly lower SPM for longer distances, higher for sprints. var estimatedSpM = Math.max(15, Math.min(40, 25 + (dragFactor – 120) * 0.1 – (watts – 250) * 0.02)); estimatedSpM = Math.round(estimatedSpM); estimatedTimeDisplay.textContent = formatTime(totalSeconds); pacePer500mDisplay.textContent = formatPace(paceSecondsPer500m); estimatedWattsDisplay.textContent = watts; estimatedSpmDisplay.textContent = estimatedSpM; updateChart(); } function updateDragValueDisplay(value) { document.getElementById('dragFactorValue').textContent = value; } function resetCalculator() { userWeightInput.value = 80; distanceInput.value = 500; dragFactorInput.value = 120; updateDragValueDisplay(120); userWeightError.textContent = ''; distanceError.textContent = ''; dragFactorError.textContent = ''; calculatePerformance(); } function copyResults() { var resultsText = "Concept 2 Erg Weight Impact Results:\n\n"; resultsText += "Inputs:\n"; resultsText += "- Your Weight: " + userWeightInput.value + " kg\n"; resultsText += "- Distance: " + distanceInput.value + " m\n"; resultsText += "- Drag Factor: " + dragFactorInput.value + "\n\n"; resultsText += "Estimated Performance:\n"; resultsText += "- Total Time: " + estimatedTimeDisplay.textContent + "\n"; resultsText += "- Pace (min/500m): " + pacePer500mDisplay.textContent + "\n"; resultsText += "- Estimated Watts: " + estimatedWattsDisplay.textContent + " W\n"; resultsText += "- Estimated Stroke Rate: " + estimatedSpmDisplay.textContent + " spm\n\n"; resultsText += "Formula Assumptions: Time is influenced by distance, drag factor squared, and a slight efficiency adjustment based on weight. Watts are estimated based on power required for time and drag factor."; var textArea = document.createElement("textarea"); textArea.value = resultsText; document.body.appendChild(textArea); textArea.select(); try { document.execCommand("copy"); alert("Results copied to clipboard!"); } catch (e) { alert("Failed to copy results. Please copy manually."); } textArea.remove(); } function createChart() { var availableDragFactors = [100, 110, 120, 130, 140, 150]; var chartData = []; var baseDistance = 2000; // Use 2000m for chart example availableDragFactors.forEach(function(df) { var weight = parseFloat(userWeightInput.value) || 80; // Use current weight or default var weightFactor = 1 – (weight / 1000); if (weightFactor < 0.9) weightFactor = 0.9; var totalSeconds = CONSTANT_FACTOR * (baseDistance / (df * df)) * weightFactor * baseDistance; var watts = WATT_CONSTANT * Math.pow(baseDistance / totalSeconds, 3) / df; if (isNaN(watts) || !isFinite(watts) || watts <= 0) watts = 0; chartData.push({ dragFactor: df, watts: Math.round(watts), timeSeconds: totalSeconds }); }); var timeLabels = chartData.map(function(d) { return formatTime(d.timeSeconds); }); var wattValues = chartData.map(function(d) { return d.watts; }); var dragFactorLabels = chartData.map(function(d) { return d.dragFactor; }); chart = new Chart(ctx, { type: 'line', data: { labels: dragFactorLabels, datasets: [{ label: 'Estimated Watts', data: wattValues, borderColor: 'rgb(255, 99, 132)', backgroundColor: 'rgba(255, 99, 132, 0.2)', fill: false, yAxisID: 'y-watts', tension: 0.1 }, { label: 'Estimated Time (2000m)', data: timeLabels, // Display time labels on chart borderColor: 'rgb(54, 162, 235)', backgroundColor: 'rgba(54, 162, 235, 0.2)', fill: false, yAxisID: 'y-time', // Assign to a separate conceptual y-axis if needed, or use tooltip hidden: true, // Hide this dataset line itself but keep data for tooltip tension: 0.1 }] }, options: { responsive: true, maintainAspectRatio: false, scales: { x: { title: { display: true, text: 'Drag Factor' } }, y: { // Primary Y-axis for Watts type: 'linear', position: 'left', title: { display: true, text: 'Estimated Power (Watts)' }, ticks: { callback: function(value) { return value + ' W'; } } }, y1: { // Secondary Y-axis concept for Time, primarily for tooltip info type: 'time', // Use time scale conceptually position: 'right', title: { display: true, text: 'Estimated Time (2000m)' }, // This axis is tricky to represent directly as a line with 'time' scale on a line chart. // We'll primarily use tooltips to show the time corresponding to each drag factor. // To make it work, we might need to convert time to a numerical representation or use tooltip. // For simplicity here, let's keep it hidden and rely on tooltip. display: false // Hide the secondary axis line display } }, plugins: { tooltip: { callbacks: { label: function(context) { var label = context.dataset.label || ''; if (label) { label += ': '; } if (context.dataset.yAxisID === 'y-watts') { label += context.formattedValue + ' W'; } else if (context.dataset.yAxisID === 'y-time') { label += context.raw; // 'raw' should be the time string } return label; } } } } } }); } function updateChart() { if (!chart) { createChart(); return; } var availableDragFactors = [100, 110, 120, 130, 140, 150]; var baseDistance = 2000; // Example distance for chart var weight = parseFloat(userWeightInput.value) || 80; var weightFactor = 1 – (weight / 1000); if (weightFactor < 0.9) weightFactor = 0.9; chart.data.labels = availableDragFactors; chart.data.datasets[0].data = []; // Watts chart.data.datasets[1].data = []; // Time availableDragFactors.forEach(function(df) { var totalSeconds = CONSTANT_FACTOR * (baseDistance / (df * df)) * weightFactor * baseDistance; var watts = WATT_CONSTANT * Math.pow(baseDistance / totalSeconds, 3) / df; if (isNaN(watts) || !isFinite(watts) || watts <= 0) watts = 0; chart.data.datasets[0].data.push(Math.round(watts)); chart.data.datasets[1].data.push(formatTime(totalSeconds)); // Push formatted time string }); chart.options.scales.y.title.text = 'Estimated Power (Watts)'; chart.options.scales.y1.title.text = 'Estimated Time (' + baseDistance + 'm)'; // Update title dynamically chart.update(); } // Initial calculations and chart creation document.addEventListener('DOMContentLoaded', function() { resetCalculator(); // Set default values and calculate createChart(); // Create the initial chart }); userWeightInput.addEventListener('input', calculatePerformance); distanceInput.addEventListener('input', calculatePerformance); dragFactorInput.addEventListener('input', calculatePerformance);

Leave a Comment