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- Introduced a new table `application_setting` to store configurable application options. - Implemented functions to manage CSS color settings, including loading, updating, and reading environment overrides. - Added a new settings view to render and manage theme colors. - Updated UI to include a settings page with theme color management and environment overrides display. - Enhanced CSS styles for the settings page and sidebar navigation. - Created unit and end-to-end tests for the new settings functionality and CSS management.
65 lines
3.6 KiB
Markdown
65 lines
3.6 KiB
Markdown
---
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title: "08 — Concepts"
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description: "Document key concepts, domain models, and terminology used throughout the architecture documentation."
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status: draft
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---
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# 08 — Concepts
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## Key Concepts
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### Scenario
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A `scenario` represents a distinct mining project configuration, encapsulating all relevant parameters, costs, consumption, production outputs, equipment, maintenance logs, and simulation results. Each scenario is independent, allowing users to model and analyze different mining strategies.
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### Parameterization
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Parameters are defined for each scenario to capture inputs such as resource consumption rates, production targets, cost factors, and equipment specifications. Parameters can have fixed values or be linked to probability distributions for stochastic simulations.
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### Monte Carlo Simulation
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The Monte Carlo simulation engine allows users to perform risk analysis by running multiple iterations of a scenario with varying input parameters based on defined probability distributions. This helps in understanding the range of possible outcomes and their associated probabilities.
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## Domain Model
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The domain model consists of the following key entities:
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- `Scenario`: Represents a mining project configuration.
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- `Parameter`: Input values for scenarios, which can be fixed or probabilistic.
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- `Cost`: Tracks capital and operational expenditures.
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- `Consumption`: Records resource usage.
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- `ProductionOutput`: Captures production metrics.
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- `Equipment`: Represents mining equipment associated with a scenario.
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- `Maintenance`: Logs maintenance events for equipment.
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- `SimulationResult`: Stores results from Monte Carlo simulations.
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- `Distribution`: Defines probability distributions for stochastic parameters.
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- `User`: Represents application users and their roles.
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- `Report`: Generated reports summarizing scenario analyses.
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- `Dashboard`: Visual representation of key performance indicators and metrics.
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- `AuditLog`: Tracks changes and actions performed within the application.
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- `Notification`: Alerts and messages related to scenario events and updates.
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- `Tag`: Labels for categorizing scenarios and other entities.
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- `Attachment`: Files associated with scenarios, such as documents or images.
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- `Version`: Tracks different versions of scenarios and their configurations.
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### Detailed Domain Models
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See [Domain Models](08_concepts/08_01_domain_models.md) document for detailed class diagrams and entity relationships.
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## Data Model Highlights
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- `scenario`: central entity describing a mining scenario; owns relationships to cost, consumption, production, equipment, and maintenance tables.
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- `capex`, `opex`: monetary tracking linked to scenarios.
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- `consumption`: resource usage entries parameterized by scenario and description.
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- `parameter`: scenario inputs with base `value` and optional distribution linkage via `distribution_id`, `distribution_type`, and JSON `distribution_parameters` to support simulation sampling.
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- `production_output`: production metrics per scenario.
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- `equipment` and `maintenance`: equipment inventory and maintenance events with dates/costs.
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- `simulation_result`: staging table for future Monte Carlo outputs (not yet populated by `run_simulation`).
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- `application_setting`: centralized key/value store for UI and system configuration, supporting typed values, categories, and editability flags so administrators can manage theme variables and future global options without code changes.
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Foreign keys secure referential integrity between domain tables and their scenarios, enabling per-scenario analytics.
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### Detailed Data Models
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See [Data Models](08_concepts/08_02_data_models.md) document for detailed ER diagrams and table descriptions.
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