# Presentation: 297132

## Panel Discussion on V&V/UQN. R. Aluru

- Panel Discussion on V&V/UQN. R. Aluru

## V&V Challenges

**Approach: **Identify key phenomena and rank their importance; Verification using tier-1 (single physics), tier-2 (coupled physics), and tier-3 (system level)
**Challenges: **Lack of modules/codes/analytical expressions for some physical phenomena; Verification can be challenging for tier-2 and tier-3

**Verification**

**Approach: **Identify key phenomena and rank their importance; Validation using tier-1 (single physics), tier-2 (coupled physics), and tier-3 (system level); Use experimental data from literature, Sandia and in-house experiments
**Challenges: **Lack of data for some physical phenomena; Validation can be challenging for many examples

**Validation**

## UQ Challenges

**Questions:**
- What input uncertainties are the most important?
- How does uncertainty in microstructure affect macroscopic membrane response? Uncertainty in dimensions?
- How does uncertainty in microstructure propagate into the force-history response and thus into structural response?

**Criterion for success:** Comparison to uncertainty experiments

**Challenges: **Propagating uncertainty across scales and physics, computational size and cost**,** careful control of number of uncertain  variables

- Young’s modulus for polysilicon as measured by various research group over the years [J. V. Clark, Ph.D. thesis, 2005].

## Verification Techniques

** ****Structural-Thermal-Electrostatics**
**Coupling  **

**Tier III Example**

## Validation Techniques

| Phenomena  | Source of Validation Data  |
| --- | --- |
| Tier 3 (System-Level Validation)

Electro-mechanical response with  dielectric charging and environmental effects

Shock response

Materials characterization and surface roughness evolution
 | 

Purdue experiments with actual RF MEMS  in the range of 25-125C and different humidity levels

Purdue experiments on actual RF MEMS structures  for a range of accelerations and temperatures from -55C to 75C.

Purdue experiments with TEM and AFM on evolution of grain size, orientation, defects, and surface roughness |

## UQ Techniques

- Generalized Polynomial Chaos

- Stochastic Collocation Methods

- + Easy to implement
- + Minor changes to code
- ─ Not as efficient as Galerkin

- ─ Harder to implement
- ─ Significant changes to code
- + More efficient than collocation

- Choice of inputs
- from collocation

- Solver

-  *Good solution for LAMMPS*
-  *Good starting point for other codes*

-  *Better for FVM / MPM codes*
-  *Optimization beyond collocation*

- realizations

## How we will use V&V and UQ to guide and set priorities for research activities

- Identifying key phenomena and ranking their importance is largely driven by V&V and UQ

- Sensitivity/UQ will determine what inputs are important to models – example: role of accomodation coefficients in rarefied gas damping

| Modeled Phenomena | Algorithm or Solver | Test Problems |
| --- | --- | --- |
| Tier I (Individual)
1. Drift diffusion charge transport 

2. Atomistic-level computation of mechanics | 
FVM

MD/LAMMPS | 
Analytic solutions for drift -diffusion for known potential field
Comparison of wire/beam bending with in-house MD codes, GRASP |
| Tier II (Coupled)
1. Electrostatics+linear mech.   
           response
2. Fluid-structure interaction | 
FVM+MPM

FVM+MPM | 
Published solutions (44 - 47)

Comparison with ADINA |

| Modeled Phenomena | Importance | Model Adequacy | Comments |
| --- | --- | --- | --- |
| 1. Electrostatics
 | High | Adequate | Large microelectronics literature and adequate data |
| 2. Stiction:
a. Roughness evolution
b. Capillary condensation | 
High
High | 
Inadequate
Inadequate | Few detailed models or simulations for roughness evolution, condensation. |
| 3. Electro-thermo-mech. response:
a. Linear
b. Nonlinear  | 

High
High | 

Adequate
Inadequate | Classical electro-mech. response well understood

Interaction of microstruct with continuum not well understood. |

## Far-Reaching V&V/UQ Issues

- Electrostatic pull-in in MEMS leads to discontinuities in the random domain; Need to develop efficient stochastic algorithms for non-smooth functions in the random domain
- Explore easier ways of implementing UQ
- New software paradigms for automating UQ implementation
- Extensive experimental data is needed for UQ /Validation
- Education, teaching and training new generation of students in V&V/UQ