Ben Bartling bbartling

open-fdd default equations for energy penalty

It is structured by equipment type, starting from the zone level and moving up to the central plant. Within each category, the rules are ordered by difficulty to implement: starting with the "low-hanging fruit" (simple boolean logic, schedules, and basic setpoint math) down to the more complex FDD rules (requiring thermodynamic models, enthalpy, or network-level data rollups).

Easy FDD Energy Penalty Equations (open-fdd TODO)

1. General & Override Faults (Easiest to Implement)

These rules apply across multiple equipment types and rely on simple binary states, schedules, or BAS overrides, making them the easiest FDD rules to deploy.

Open-FDD Expression Rule Cookbook — DBO-Oriented Translation

This document recasts the Open-FDD expression rule cookbook into a Digital Buildings Ontology (DBO) style.

It is not a claim that DBO itself stores or executes fault rules. In DBO, the ontology primarily models entities, fields, translations, and relationships, while the fault logic still lives in your analytics engine (for example, Open-FDD, pandas, SQL, or another rules engine).

So the conversion here means:

Replace Brick-class-centric rule inputs with DBO field names.
Preserve the original fault logic as close as possible.

OpenClaw Prompts - Build Your Own AI Assistant

Prompts to recreate each piece of the OpenClaw system. Use these with any AI coding assistant.

1. Personal CRM "Build a personal CRM that automatically scans my Gmail and Google Calendar to discover contacts from the past year. Store them in a SQLite database with vector embeddings so I can query in natural language ('who do I know at NVIDIA?' or 'who haven't I talked to in a while?'). Auto-filter noise senders like marketing emails and newsletters. Build profiles for each contact with their company, role, how I know them, and our interaction history. Add relationship health scores that flag stale relationships, follow-up reminders I can create, snooze, or mark done, and duplicate contact detection with merge suggestions. Link relevant documents from Box to contacts so when I look up a person, I also see related docs."

2. Meeting Action Items (Fathom)

🧠 Executable Brick: Embedding Python into RDF for Automatic Optimization

Future Vision for Open-FDD

🚀 Concept

Today, Brick describes what equipment exists in a building.

🎮 AI Voice Cutscene Generator (WSL + Edge-TTS)

Generate cinematic, human-sounding AI dialogue for game cut scenes using Microsoft Neural Voices, completely scriptable from Python.

The script takes a dialogue script with two characters, generates separate voice lines, then merges them into a single cutscene_edge.wav ready for Unity, Unreal, Godot, etc.

⚠️ This uses Microsoft’s neural TTS over the internet via Edge-TTS. Text is sent to Microsoft’s service; audio comes back. No API key required.

Works great with:

BACnet Diagnostic Tools

Two scripts for discovering, auditing, and manually testing BACnet networks.

1. Install Requirements

Run this once to get the required libraries:

pip install bacpypes3 ifaddr rdflib

	import pandas as pd
	import numpy as np
	import matplotlib.pyplot as plt
	import os

	# Load the CSV data into a DataFrame
	df = pd.read_csv("Merged_Weather_System_Data.csv")

	# Convert timestamp to datetime and set as index
	df['ts'] = pd.to_datetime(df['ts'])

	from __future__ import annotations

	import argparse
	import os
	import re
	import requests
	import subprocess
	import sys
	from pathlib import Path
	from typing import List, Tuple, Optional, Callable, Dict

	import asyncio
	import BAC0

	"""
	not tested yet
	"""

	async def main():
	bacnet = BAC0.lite()