Which AI is actually good for complex engineering calculations (strength of materials, chem, process stuff)?

Evaluating Artificial Intelligence Tools for Advanced Engineering Calculations: A Professional Perspective

In the realm of engineering and chemical process analysis, the quest for reliable AI assistance extends beyond illustrative examples, delving into complex, real-world computations. Engineers often seek AI tools that can serve as intelligent collaborators—aid in derivations, organize procedural steps, and uphold accuracy—without substituting rigorous verification. This article explores the suitability of current AI models for sophisticated engineering calculations, focusing on their capabilities in strength of materials, chemistry, and process engineering.

Understanding the Practical Needs

Unlike solving basic algebra or simple equations, advanced engineering calculations involve multistep derivations, unit management, and adherence to industry standards. For example:

• Strength of Materials: Stresses, safety factors, component sizing, and stress analysis require precise step-by-step solutions.

• Chemical Engineering: Balancing complex chemical equations, calculating stoichiometry, mass and energy balances, diffusion coefficients, and heat transfer parameters.

• Process Engineering: Modeling distillation columns, heat exchangers, and process simulations necessitate accurate, detailed calculations.

Current AI Capabilities and Limitations

Many engineers have turned to conversational AI models like ChatGPT for conceptual explanations and initial problem framing. While these tools excel at clarifying concepts and providing high-level guidance, their reliability diminishes with increasing calculation complexity. Common issues include:

• Omission of intermediate steps: Leading to opaque derivations that hinder validation.

• Inconsistent numerical results: Variations within derivations, often due to overlooked units or assumptions.

• Fabrication of formulas or standards: AI-generated content may include non-existent procedures, risking inaccuracies.

• Handling of Units: Inconsistent or incorrect unit conversions can significantly distort results.

Ideal AI for Engineering Calculations

An effective “calculation buddy” should demonstrate:

• Step-by-step transparency: Showing derivations clearly for easy verification.

• Robust unit management: Recognizing, converting, and checking units throughout the process.

• LaTeX output capability: Facilitating integration into reports and documentation.

• Compatibility with high-level engineering disciplines: Handling university-level and professional calculations in strength analysis, thermodynamics, mass and energy balances, etc.

Current Tools and Practices

While no AI currently fulfills all these requirements perfectly, some approaches can improve reliability:

• Specialized calculation software combined with AI: Using established engineering tools (e.g., MATLAB, Aspen Plus,