Virtual Excavator Simulator

Overview

A real-time, browser-based excavator simulator with interactive terrain deformation. Operate the boom, arm, bucket, and tracks using keyboard controls or on-screen joystick pads. The terrain deforms as the bucket digs, particles kick up on contact, and excavated material accumulates as dirt piles. An auto dig cycle demonstrates the full digging sequence automatically.

Two on-screen joystick pads provide the same control via mouse or touch — left pad for boom and arm, right pad for bucket and swing.

Features

Machine — Articulated excavator with crawler tracks, counterweight, cab, boom, arm, and a four-tooth bucket with a cutting edge. Three hydraulic cylinders (boom, arm, bucket) animate with visible extension and retraction.

Terrain — A 200-segment deformable ground surface. The bucket physically displaces soil on contact, creating a pit. Dust particles spawn at the dig point and dirt accumulates as piles at the dump location.

Camera — Smooth side-view camera that follows the machine as it tracks along the terrain.

Auto Dig — A six-phase automated cycle: position → dig in → lift → carry → dump → reset. Repeats continuously until stopped. Dig count and total dirt moved are tracked in the stats bar.

Dashboard — Live boom, arm, bucket, and swing angles; cylinder position bars; timestamped activity log; and running totals for completed dig cycles, dirt volume moved, and elapsed simulation time.

This is an interactive laboratory designed to help users explore and understand charge-carrier flow inside semiconductors from multiple perspectives.

• Electron Flow — Visualizes the movement of electrons and holes, including thermal motion, drift, and scattering, in real time using Canvas.
• 4 Visualization Modes — Explore semiconductor behavior through Carrier Drift, Crystal Lattice, Thermal Motion, and Electric Field views.
• Material Models — Compare Intrinsic, N-type, and P-type semiconductors.
• Energy Bands — Visualize the concepts of the Valence Band, Band Gap, and Conduction Band.
• P–N Junction — Explore P-type and N-type regions, the depletion region, and the basic concept of electrical bias.
• MOSFET Channel — Follow the process Gate Voltage → Electric Field → Channel Formation → Carrier Drift → Drain Current.
• Concept Map — Understand the relationship Crystal Lattice → Energy Bands → Charge Carriers → Electric Field → Electrical Current.
• Interactive Parameters — Directly adjust Electric Field, Carrier Density, Temperature, Scattering, and Hole Fraction.
• Simulation Controls — Experiment with Inject Carriers, Pause, Reverse Field, and Reset.
• Real-Time Telemetry — Monitor Electrons, Holes, Drift Index, Scatter Events, and Current Trend as the simulation runs.
• Electron vs. Conventional Current — Visually observe the difference between the electron drift direction and the conventional current direction.
• Educational Conceptual Simulator — This is not a TCAD or SPICE tool for real semiconductor process or device design. It is designed as an educational conceptual simulator for understanding the fundamental principles of semiconductor charge transport.

Overview

An interactive, browser-based simulation of a traction elevator control system, showing how a Programmable Logic Controller processes inputs, executes ladder logic, drives outputs, and manages safety interlocks in a continuous scan cycle. The simulation runs a five-floor elevator with real physics — acceleration, deceleration, door timing, and counterweight movement — while exposing the underlying control logic in real time.

Content

Live Operation — The main view shows an animated elevator shaft with a moving car, counterweight, and spinning sheave. Hall call buttons on each floor and car operating panel buttons inside the cab register requests. The controller dispatches the car to the nearest pending call, smoothly accelerates and decelerates using configurable speed and acceleration parameters, levels at the target floor, releases the brake, and opens the doors automatically. A bottom console shows the PLC scan cycle animating through its four phases, live logic bar graphs for position, velocity, and door state, a timestamped event log, and the current state of the four main output commands — motor up, motor down, brake, and door open.

PLC I/O & Ladder — Shows the input and output racks with 24 VDC digital I/O addresses and their current on/off states, updated live from the simulation. A simplified ladder logic diagram displays five rungs covering the up motion enable, down motion enable, brake application, door open, and dispatcher dispatch coils — each with their contact conditions lighting up as the simulation runs.

PLC Scan Cycle — Explains and animates the four-phase PLC scan: read inputs, execute program, write outputs, housekeeping. A process image table lists all key addresses and their current values sampled live from the simulation.

Safety Chain — Shows the series of interlocks that must all be healthy before motion is permitted — emergency stop closed, doors locked, limit switches normal, brake monitored, and drive healthy. Training fault injection buttons simulate a door interlock failure, a drive inverter fault, and a limit switch fault, showing how the controller removes motion commands and applies the brake in response. A clear button restores all devices.

Controls — Mode switch between AUTO and MANUAL, sliders for maximum speed (0.4–2.0 m/s), acceleration rate, and door dwell time, manual jog up/down buttons (MANUAL mode only), emergency stop toggle, and controller reset.

Disaster & Collision Simulator — Overview

A browser-based, single-file interactive visualization suite covering six categories of physical disaster and collision events. Each simulation runs as a real-time Canvas animation with adjustable parameters, live data readouts, and physics-informed behavior — no dependencies beyond the fonts.

Simulations

🌍 Seismic Wave

Models the propagation of P-waves (primary, compressional) and S-waves (secondary, shear) radiating from a user-placed epicenter. Surface structures respond dynamically to ground motion — buildings accumulate stress, lean, and eventually collapse as shaking intensity exceeds their structural capacity. An embedded seismograph panel plots ground displacement in real time, replicating the output of a broadband seismometer.

🌊 Tsunami

Simulates a shallow-water bore surge making landfall after a submarine seismic event. Wave shoaling compresses and amplifies the wave front as it transitions from deep ocean to the continental shelf. Floating debris objects respond to hydrodynamic drag and inundation depth, illustrating the destructive load-carrying capacity of the surge beyond the initial wave impact.

☄️ Meteor Impact

Renders a hypervelocity atmospheric entry and ground impact. The impactor follows a ballistic trajectory with a thermal trail, vaporizing on contact and excavating a crater scaled to diameter, velocity, and material density. Concentric shock rings propagate outward from the impact point, and ejecta particles follow ballistic arcs under gravity, replicating the mechanics documented in impact cratering studies.

🔥 Wildfire Spread

Implements a stochastic cellular automaton on a grid of fuel cells, where ignition probability for each cell is computed from neighbor fire state, wind vector alignment, and fuel moisture content — directly reflecting the Rothermel fire behavior model. Wind direction and magnitude are adjustable in real time, and new ignition points can be placed interactively to study fire front interaction and spotting behavior.

🏗️ Building Collapse

Demonstrates progressive structural failure initiated at a user-defined weak floor. Once the failure floor loses integrity, gravitational load redistributes upward through the remaining structure, triggering a cascading collapse sequence floor by floor. Debris accumulates at ground level with restitution physics, modeling the pancake-collapse mechanism observed in seismically damaged reinforced-concrete structures.

🚗 Vehicle Crash

Applies conservation of momentum to a configurable two-vehicle head-on collision. Crumple zone deformation is proportional to closing speed and mass ratio, extending the collision duration to reduce peak deceleration force — the core principle of modern passive safety design. Delta-V (change in velocity) is computed and displayed as the primary injury-severity indicator, consistent with real-world crash reconstruction methodology.

Sorting — 6 Algorithms

🫧 Bubble Sort — Compares adjacent elements and "bubbles" the larger value to the right. Each pass is colour-coded to show the maximum value settling at the end. Live counters track comparisons (red), swaps (yellow), and sorted elements (green).

🎯 Selection Sort — Scans the unsorted region for the minimum value (blue pivot · orange current minimum) and swaps it to the front. Always performs O(n²) comparisons, but keeps the number of swaps to a minimum.

📌 Insertion Sort — Takes the next element and inserts it into its correct position within the already-sorted region. An adaptive algorithm that approaches O(n) on nearly-sorted arrays.

🔀 Merge Sort — Recursively splits the array in half, then merges the halves back together. The merge step — comparing two sub-arrays and placing elements in order — is shown as blue bars. Stable sort with a guaranteed O(n log n) time.

⚡ Quick Sort — Picks a pivot (orange) and partitions the array so smaller values go left and larger values go right, then recurses on each side. Average O(n log n), worst case O(n²). Once a pivot's final position is confirmed, it turns green.

🏔️ Heap Sort — Builds a Max-Heap from the array (heapification), then repeatedly extracts the root (maximum). In-place sort with a guaranteed O(n log n) time.

Graph — 4 Algorithms

🌊 BFS — Explores outward from the start node one layer (hop) at a time. Guarantees the shortest path by hop count in unweighted graphs, then traces the route back through parent pointers once the goal is reached.

🔍 DFS — Recurses as deep as possible along each branch before backtracking. Does not guarantee the shortest path, but is the foundation for connectivity checks, topological sorting, and cycle detection.

🗺️ Dijkstra — Finds the true shortest distance in a weighted graph. A priority queue ensures the lowest-cost node is always processed first; edge weights are displayed inside each node.

⭐ A* — Dijkstra plus a heuristic (Euclidean distance to the goal). The formula f(n) = g(n) + h(n) steers the search toward the target, making it faster than Dijkstra in practice. Guarantees an optimal path as long as the heuristic is admissible.