Free NREL Tool Helps Engineers Maximize R&D Investments
The National Renewable Energy Laboratory’s open-source, Python-based tool helps engineers plan research and development projects. The free tool can help engineers estimate project costs and make strategic decisions.
Engineers can leverage a new open-source tool to gain critical insight into their research and development (R&D) processes. Its capabilities help inform decision-makers and ensure project progression is as straightforward, cost-effective, and risk-free as possible.
Engineers planning a project. Image used courtesy of Oak Ridge National Laboratory
The National Renewable Energy Laboratory (NREL), overseen by the U.S. Department of Energy, has developed a Python-based open-source software package called Tyche. It’s available on GitHub under the Massachusetts Institute of Technology (MIT) license with few reuse restrictions.
Named after the Greek goddess of fortune, success, and prosperity, Tyche maximizes R&D investments by identifying potential risks and benefits of various strategies. NREL built it with decision-makers in mind, so it aggregates and analyzes data to optimize scenario exploration.
What Does Tyche Do?
Tyche operates on a general, replicable workflow. Engineering decision-makers must first input the scope and conditions of their R&D investment. The Tyche codebase then leverages data on the technology, past projects, and expert elicitation on performance to establish a contextual framework.
Although expert elicitation isn’t essential, engineers can leverage it if uncertainties impact the simulation’s accuracy too substantially. Tyche uses insufficient data to distinguish optimal input probabilities.
Tyche allows collaboration among decision-makers. Image used courtesy of NREL
The flow of information then moves through a techno-economic model to simulate the technology’s technical operation so engineers can tell whether its performance makes up for operating costs. It also helps them determine how significant the return on investment (ROI) will likely be.
The codebase leverages ensemble simulation to evaluate potential scenarios further to calculate cost-based metrics. It synthesizes a range of possible outcomes so engineering decision-makers can identify the ideal strategy. Merging multimodel predictions this way improves accuracy significantly. This process doesn’t require extensive funding or space despite its magnitude.
Stochastic optimization—random variable generation for objective function improvement—is another way Tyche calculates cost-based metrics. This method improves accuracy when randomness is present, so it’s ideal for engineers dealing with uncertainty.
The result of this entire process is a visual, measurable representation of R&D investments. This way, engineers can compare individual strategies at multiple levels. They can review likely scenarios, pinpoint potential areas of improvement, and identify uncertainty.
How Tyche Maximizes R&D Investments
Engineers can use Tyche to inform their investment decisions whether they research improvements on existing technology or develop something entirely new. It aligns research goals with data-driven outcomes to optimize R&D budgets across multiple projects.
People can use ensemble simulation, techno-economic modeling, and stochastic optimization to detect potential bottlenecks, identify uncertainty, and improve objective function even when unexpected variables are present. This tool ensures progression is cost-effective and has minimal risk.
Errors, material variability, and unpredictable conditions can restrict progression. On average, a one-unit increase in the World Uncertainty Index—a global tracking tool—lowers R&D investments by 40% and patent applications by 88% annually. Uncertainty negatively impacts engineering R&D, and fortunately, Tyche can identify outcomes while accounting for it.
Since Tyche considers uncertainty while recognizing investment risks and advantages, engineers can accurately evaluate how their R&D decisions will pan out. They can even compare various avenues to determine the best path forward.
Information processed through Tyche software. Image used courtesy of NREL
Tyche offers measurable, reproducible analytical support to provide engineers with critical insight, safeguard them against risks, and optimize their technology’s performance. Additionally, it can help them save time and money at every exploration stage, maximizing R&D investments.
This software package is free with a flexible license, meaning engineers can use it with few reuse limitations. Ultimately, the open-source nature further maximizes R&D investments because there’s no need to pour money into an expensive third-party service or tool to gain clarity on decision-making.
Should Engineers Use Tyche in R&D Investment?
Considering Tyche is a free, open-source tool, there’s virtually no reason engineers shouldn’t integrate it into their current R&D. Engineering R&D investments are becoming more significant each year. Experts believe they will increase at a 10% annual compound annual growth rate from 2022 to 2026. As they grow, so should engineer’s accuracy and speed regarding technological progression.
Engineers who want to remain competitive and resilient should consider leveraging a tool like Tyche to inform decision-making and improve their R&D processes. At the very least, it clarifies their technology’s performance and cost.
The Importance of Optimizing R&D Investments
Tyche is one of the few open-source tools capable of informing decisions while accounting for errors, variables, and external conditions. Optimization is essential because engineering R&D investments will continue to grow substantially every year—and uncertainty negatively impacts them.