Fluid Dynamics Engineer
Lead UX Designer — Human-Centered Simulation
Designing a human-centered simulation experience to democratize computational fluid dynamics (CFD) for engineers and designers without sacrificing technical rigor.
Team: UX Design, Development, Product Portfolio
Primary Role: UX Design, UX Research
Duration: 2 years, and still going
Problem Statement
Computational Fluid Dynamics tools have traditionally been built for expert analysts, resulting in steep learning curves, complex workflows, and limited accessibility for non-expert users. Engineers and designers often struggled with setup complexity, unclear terminology, and low confidence in interpreting results.
The opportunity was to rethink CFD through a human-centered UX lens, shifting complexity from the user to the system.
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My Role
As the Lead UX Designer, I led the end-to-end design strategy, shaping how advanced simulation tools could become intuitive, learnable, and trustworthy. I worked closely with CFD engineers and product stakeholders to translate complex physics into accessible user experiences.
Research & Discovery
The Fluids UX initiative was grounded in a research-driven, iterative design process embedded within SIMULIA R&D. I conducted qualitative research with CFD experts and non-expert users to understand mental models, workflows, and pain points. Research revealed that users were not intimidated by complexity itself, but by unclear feedback, unfamiliar terminology, and a lack of guidance during critical decision points.
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Key Insights
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Users needed clearer feedback to trust simulation results
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Terminology created barriers for non-experts
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Setup workflows did not match how users think or explore designs
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This process, as we worked, helped us build a framework for an Agile UX Research-driven design and development cycle that allowed for iteration while maintaining clarity across a complex product ecosystem.
Each release cycle starts with research, not assumptions. We interview users, watch them set up models, run simulations, and note where friction hides. Often, it’s not in what people don’t know. It’s in what the interface assumes they already understand.
In the picturee you can see, instead of a one-way waterfall, research added input points at multiple stages throughout the process..
Insights from Discovery research, flowed into Define Requirements, then into Design. Those were then tested in Design validation research and then sent into Development. ​​​​
Insights and Design Principles
Based on research insights, we established a set of human-centered design principles that guided all our decisions:
1. User Work Model vs. System Model
Users often bring strong expectations shaped by their prior tools and workflows. Our design approach focused on aligning the product’s logic with how users naturally think and act, not the other way around. Key takeaway: Design should adapt to the user’s work model, not demand they adopt yours.​
2. Language & Terminology
The words we use shape how approachable a product feels. We refined terminology to ensure technical accuracy while improving clarity and inclusivity across different experience levels. Key takeaway: Clear language is usability.
3. Learning Curve & Onboarding
In simulation tools, the first few minutes define the user’s relationship with the product. We focused on creating an onboarding flow that encourages discovery and builds confidence step by step. Key takeaway: Learning should feel guided, not gated.
4. Trust & Confidence in Application
For complex tools, how the system communicates matters as much as what it computes. We rethought how the interface responds to uncertainty, turning errors into feedback and feedback into trust. Key takeaway: Confidence is a UX outcome.
Problem Statement
Computational Fluid Dynamics tools have traditionally been built for expert analysts, resulting in steep learning curves, complex workflows, and limited accessibility for non-expert users. Engineers and designers often struggled with setup complexity, unclear terminology, and low confidence in interpreting results.
The opportunity was to rethink CFD through a human-centered UX lens, shifting complexity from the user to the system.
As the leading cause of death in the United States, coronary heart disease affects millions of people each year. Approximately 50,000 open-heart surgeries are performed annually, many of which involve complex and demanding procedures.
Key Takeaways
Following cardiovascular surgery, many individuals experience drastic lifestyle changes and often require daily support from a family member. For those without a caregiver, or whose family members are uninformed about their health, a smart assistant can play a crucial role in managing recovery activities and maintaining communication with loved ones.
Our Mission was clear:
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Help cardiovasuclar disease patients failitate a better recovery journey after surgery.
Ideation and Prototyping
Major cardiovascular incidents predominantly affect individuals who are 65 years old or older. Recognizing that our users have a preference for physical presence within their homes, we aim to develop a solutipn that fosters an emotional connectiion with patients during their most vulnerable mements.
Form Iterations​
We designed a home assistant that interacts with our users through both its physical presence and an integrated digital interface.
Systems Mapping
We designed a device that mapped to a post CVD patient's daily schedule by working with them.
We observed that surgery dramatically alters a persons life and observed the numerous limitations they face post-surgery. From this understanding, we conceived LIVIA as not just a companion but also a facilitator for their daily life.
A key feature of LIVIA is its capability to integrate with other intelligent devices. Our first MVP includes a smart ECG monitor designed to work in conjunction with LIVIA for everydat monitoring.
Refined User Journey
The depicted user experience illustrates how LIVIA serves as a bridge between patients and their loved ones, enabling meaningful connection even when they are physically distant but deeply care. Additionally, LIVIA is designed to seamlessly integrate with other smart devices, creating a supportive and connected recovery ecosystem.
Final Product
More Iterations and Redesign
Based on several rounds of critics and further talking to potential users, we made several design changes on the interface.
Since our users primarily were between the ages of 45 and 75, many experienced difficulty recognizing small on-screen content. In response, we updated the interface with larger fonts and more distinct color contrasts to ensure it is easier to read and more accessible for users with these conditions.
LIVIA Device
The final step was to build a functional prototype. It consisted of a Raspberry Pi mini connected to a 2.8-inch circular display, LED strip lights, a servo motor for actuation, and ultrasonic sensors to detect the patient’s proximity.
ECG Patch
To test the device pairing function, we also built an ECG patch to monitor a persons pulse and transmit information realtime.
