ABOUT our featured services
Steady-state & dynamic system modeling & simulation
We provide physics-based* steady-state and dynamic modeling and simulation for various thermal systems. These systems may include but not limited to vapor compression systems, absorption heat pumps, gas turbine and fuel cell power plants, autothermal or steam reforming-based H2 generation systems, and energy storage systems. We can model the thermal systems with MATLAB/Simulink/Simscape, Aspen/HYSYS, Modelica, or Numerical Propulsion System Simulation (NPSS).
Example 1: Selecting next-gen refrigerant(s) for Vapor Compression Systems (VCS)
(1) Build steady-state system models for screening refrigerant candidates: We can build system models accurately simulating steady-state performance of an existing vapor compression system. A subroutine can be added to the system models to assess flammability and toxicity (ASHRAE Standard 34) of a refrigerant. Thus, one single simulation platform can evaluate the performance, system cost, flammability, and toxicity of a refrigerant at once.
(2) Conduct virtual drop-in testing in dynamic models: We are capable of developing physics-based dynamic models, enabling Software-In-the-Loop (SIL) testing for “dropping-in” a refrigerant candidate. The virtual “drop-in” tests can uncover issues associated with operation, control, and integration, reducing the required effort for experimental “drop-in” tests (step 3).
(3) Perform drop-in experimental testing: Work with our customer closely to develop test plans to verify component models and to validate overall system models and hardware behaviors for refrigerant candidates.
Example 2: concept development for an integrated compressed air energy storage/ gas turbine combined cycle: Develop various system-level models fully utilizing the equipment of the combined cycle for energy storage to reduce developmental and installation costs. For example, extract compressed air from the gas turbine compressor for energy storage to eliminate the need for a dedicated energy storage compressor. In this example, it is critical to build a compressor model with the ability of predicting compressor performance even when a large amount of compressed air is extracted. Use the model to down-select the most promising concepts
Example 3: Selecting working fluids for an Organic Rankine Cycle (ORC)
Similar to the 3-step processes for Example 1. One of the key differences between an ORC and VCS is that an ORC operates generally at much higher temperatures than a VCS does. Thus, the stability of the working fluid at high temperatures for an ORC must be considered in screening working fluids.
Related experiences
- Selected refrigerants for a mixed refrigerant system used for trailer-mounted natural gas liquefication plants
- Evaluated annual energy production for a combined cycle when cold energy storage is added.
- Developed transient system models to determine the crystallization-free operational windows for a lithium-bromide absorption chiller.
- Evaluated performance of air delivery systems for aircraft environmental control and de-icing systems at various flight altitudes
- Developed system models for 5kW fuel cell power plants to support concept inception, performance analysis, requirements flow-down, FMEA, and hazard & operability studies.
- Evaluated vapor compression systems against air refrigeration cycles for aircraft
- Simulated steady-state and transient behaviors of an evaporator with natural 2-phase flow circulation.
* Depending on availability of data, portions of the model can include empirical correlations and machine learning results.
Multi-domain modeling for MBSE
INCOSE defines MBSE as “Model-Based Systems Engineering (MBSE) is the formalized application of modeling to support system requirements, design, analysis, verification and validation activities beginning in the conceptual design phase and continuing throughout development and later life cycle phases.” A multi-domain system model is the key element for implementing MBSE. This single system model can be consistently used to support every phase of technology or product development to reduce or eliminate errors associated with changing modeling platforms and assumptions, manual inputs, or tracking complex interactions of system components by hand.
We use a single software platform (e.g., MATLAB/Simulink, Modelica, or HYSYS) to facilitate multi-domain modeling, enabling many popular analyses for product or technology development. These popular analyses often require an integration of several different domain knowledges. Example cases below illustrate the relationship between the analyses and domain knowledges.
Case 1. Evaluated value propositions of mechanical chiller-based turbine inlet air chilling systems against absorption chiller-based ones: Determining the value propositions requires the domain knowledge in cost and cash flow calculation while calculating the performance needs domain knowledge in thermal sciences. Additionally, the cost calculation requires the information of mechanical design. Therefore, Table 1 on the right shows that Case 1 requires 3 different domain knowledges: (1) thermal sciences, (2) cost & cash flow, and (3) mechanical design
Case 2. Developed dynamic system models for sCO2 cycles to support evaluation of operability and safety and development of control methods: In addition to (1) thermal sciences and (2) mechanical design, the case requires 3 additional domain knowledges: (3) time dependent behaviors for dynamic modeling, (4) rotational mechanics for simulating rotor behaviors, and (5) control engineering for the operability and control of the sCO2 plant. Case 2 in Table 1 exactly has these 5 domain knowledges checked.
Case 3. Developed steady-state and dynamic system models for LiBr absorption heat pumps to determine crystallization-free operational windows : Since the lithium bromide (LiBr) solution in a LiBr absorption heat pump can crystalize during undesired transients, modeling dynamic behaviors of the heat pump is needed to understand crystallization-free operation. The dynamic modeling requires 3 different domain knowledges (see Table 1): (1) thermal sciences, (2) mechanical design, and (3) time dependent behaviors.
Case 4. Maximizing the Net Present Value (NPV) for an E-class gas turbine combined cycle with hot sand thermal energy storage system: To determine the NPV for the plant, the case requires the domain knowledges in (1) thermal sciences, (2) cost & cash flow, and (3) mechanical design. Additionally, the case requires the domain knowledge in optimization to maximize the NPV. Therefore, Table 1 shows 4 different domain knowledges are needed for Case 4.
Table 1. Relationship between domain knowledge & analysis
Thermal Systems analyses & Solutions
In this category, we provide services in 4 areas: (1) proposal preparation, (2)technology landscaping, (3) software tools for performing system analyses, and (4) thermal-fluid analysis.
Proposal preparation
We can help our customers in two ways. First, we can provide analytical analyses to support proposal writing, including trade-offs between CAPEX and performance, system-level thermodynamic and thermal-fluid analyses, and technologies landscaping. Second, we can contribute to proposal writing in response to FOAs from various government agencies such as DOE, DoD, and ARPA-E.
Technology landscaping
We have extensive experience in conducting competitive technology landscaping for various thermal systems. Our assessment reports include costs, performance, technical challenges for interested technologies.
Software tools for performing system analyses
With extensive experience in developing multi-domain modeling using various software platforms, we have deep knowledge in selecting best tools to perform multi-domain modeling. Our recommended selection is based on customer’s specific resources and products. Additionally, we can provide custom libraries to help our customers accelerate development of their multi-domain models. These libraries may include financial calculation, system component models, and thermodynamic and transport properties of fluids. The financial calculation may include cost, cash flow, NPV, and IRR functions while the component models comprises of compressors, expanders, valves, heat exchangers, etc.
Thermal-fluid analysis
Conduct thermal-fluid analysis on overall thermal systems. After determining critical parts to performance on the overall analysis, perform detailed thermal-fluid analysis on these critical parts. The detailed analysis may include CFD analysis.
Related Experience
- Wrote proposals in response to DOE, ARPA-E, and DoD’s FOAs
- Designed processes and sized components for compressed air energy storage, sCO2, fuel processing, absorption heat pump, and vapor compression systems.
- Conducted technology landscaping for H2 production, power generation, air cooling/dehumidification, and thermal energy storage.
