miniWIZ (Research Advisor):
TURNING OLD PROBLEMS INTO HIGH VALUE LOW-CARBON PRODUCTS
- 40% of world’s resources & energy are used to construct + operate buildings, 8% alone in Concrete production
- Less than 20% of building materials are recyclable, 90% of global footprints are associated with developed urban centers
- 70% of World’s GDP is based on building activities. Recycled building material has the least carbon footprint and encouraged by all green government policies
- Construction material production and thermal control during building operation are the biggest energy cost drivers in buildings
- Warehouse building typology has the highest covered surface area of any building typology in the world, which is also the least energy efficient building type.
Transforming Human Desire into Earth Saving endeavor, MINIWIZ innovation turns trash into desired products.
We create a niche with endless possibility of growth by developing and marketing eco products into different market segments based on new sustainable material technology. As a Creative Partner in Today’s Low Carbon revolution, we transform these innovative materials into real consumer facing commercial products/solutions today
We focus on the theories and algorithms development of adaptive mesh-free methods for practical industrial problems. This work supplies new theoretical results underpinning meshless collocation methods. In particular, we study different variations of asymmetric strong collocation technique. We continue to develop and improve the adaptive trial space selection algorithms for solving large-scale engineering problems efficiently.
Adaptive trial space selection in action [WMV]
- Residual reduction of overdetermined Kansa's method [WMV]
Our previous research focused on inverse problems of various kinds in which the studied in Cauchy problem of elliptic operators are the most relevant. More recently, we apply the boundary control technique for solving this inverse problem. The high computational cost is reduced by a coupling with the method of fundamental solutions. Moreover, the method can successfully recover harmonic functions with boundary singularities from noisy Cauchy data.
literatures on numerical differentiation featured with plenty of nicely
calculated practical solutions, but most research papers on this topic
is limited to one-dimension or highly structured grids. Numerical methods
for higher dimensions are very limited. Our research supplies a new, efficient,
practical alternative for scientists and industrialists who need to compute
numerical differentiation from real-life, large-scale and noisy multivariate