公开(公告)号：WO2012019022A3

公开(公告)日：2012-05-18

申请号：PCT/US2011046620

申请日：2011-08-04

Applicant: UNIV CALIFORNIA ,  MEZIC IGOR ,  EISENHOWER BRYAN A

Inventor： MEZIC IGOR ,  EISENHOWER BRYAN A

IPC: G05B23/02

CPC classification number: G01R19/00 ,  F24F11/47 ,  F24F2011/0094 ,  G05B15/02 ,  G06F17/5004

Abstract: Systems and methods are disclosed for analyzing building sensor information and decomposing the information therein to a more manageable and more useful form. Certain embodiments integrate energy-based and spectral-based analysis methods with parameter sampling and uncertainty/sensitivity analysis to achieve a more comprehensive perspective of building behavior. The results of this analysis may be presented to a user via a plurality of visualizations and/or used to automatically adjust certain building operations. In certain embodiments, advanced spectral techniques, including Koopman-based operations, are employed to discern features from the collected building sensor data.

Abstract translation: 公开了用于分析建筑物传感器信息并将其中的信息分解成更易于管理和更有用的形式的系统和方法。 某些实施例将基于能量和基于频谱的分析方法与参数采样和不确定性/灵敏度分析相结合以实现建筑物行为的更全面的视角。 该分析的结果可以通过多个可视化呈现给用户和/或用于自动调整某些建筑物操作。 在某些实施例中，采用包括基于库普曼的操作的高级光谱技术来从收集的建筑物传感器数据中识别特征。

公开(公告)号：WO03011443A3

公开(公告)日：2003-07-03

申请号：PCT/US0223462

申请日：2002-07-24

Applicant: HARVARD COLLEGE ,  STROOCK ABRAHAM D ,  DERTINGER STEPHAN K W ,  AJDARI ARMAND ,  MEZIC IGOR ,  STONE HOWARD A ,  WHITESIDES GEORGE M

Inventor： STROOCK ABRAHAM D ,  DERTINGER STEPHAN K W ,  AJDARI ARMAND ,  MEZIC IGOR ,  STONE HOWARD A ,  WHITESIDES GEORGE M

IPC: B01F5/00 ,  B01F5/06 ,  B01F13/00 ,  B01J19/00 ,  B01L3/00 ,  B81B1/00 ,  B81C1/00 ,  G01N27/447

CPC classification number: B01F5/061 ,  B01F5/0646 ,  B01F13/0059 ,  B01F2005/0028 ,  B01F2005/0621 ,  B01F2005/0636 ,  B01F2215/0422 ,  B01F2215/0431 ,  B01J2219/00889 ,  Y10T137/2224 ,  Y10T436/255

Abstract: A mixing apparatus is used to effect mixing between one or more fluid streams. The mixing apparatus generally functions by creating a transverse flow component in the fluid flowing within a channel without the use of moving mixing elements. The transverse or helical flow component of the flowing fluid or fluids can be created by weak modulations of the shape of the walls of the channel. Transverse or helical flow component can be created by grooves features defined on the channel wall. Specifically, the present invention can be used in laminarly flowing fluids. The mixing apparatus and methods thereof can effect mixing of a fluid or fluids flowing with a Reynolds number of less than about 100. Thus, the present invention can be used to mix a fluid flowing in the micro-regime. The mixing apparatus can be used to mix a fluid in a microfluidic system to significantly reduce the Taylor dispersion along the principal direction. The mixing apparatus can be used to increase the effective exposed area to promote diffusion of components between or within the fluid or fluids.

Abstract translation: 使用混合装置来实现一个或多个流体流之间的混合。 混合装置通常通过在不使用移动的混合元件的情况下在通道内流动的流体中产生横向流动分量来起作用。 流动流体或流体的横向或螺旋流动分量可以通过通道壁的形状的弱调制而产生。 横向或螺旋流分量可以通过在通道壁上定义的凹槽特征来创建。 具体而言，本发明可用于层流流体。 该混合装置及其方法可以实现以小于约100的雷诺数流动的一种或多种流体的混合。因此，本发明可以用于混合在微观状态下流动的流体。 混合装置可以用来在微流体系统中混合流体以显着减少沿主方向的泰勒色散。 混合装置可以用来增加有效暴露面积以促进流体之间或流体内部的组分的扩散。

公开(公告)号：WO2015196133A3

公开(公告)日：2016-02-25

申请号：PCT/US2015036779

申请日：2015-06-19

Applicant: UNIV CALIFORNIA

Inventor： GEORGESCU MICHAEL V ,  MEZIC IGOR

IPC: G06F15/18

CPC classification number: G06N99/005 ,  G05B23/0221

Abstract: A system and method are provided for physical data rectification using regression models. For example, the physical data may be energy infrastructure sensor data. The system may perform an estimation of sensor data during periods of data dropout using a regression model. The system may assess the accuracy of regression models through the comparison of probability distribution functions of physical data estimated using the regression model and actual physical data.

Abstract translation: 提供了使用回归模型进行物理数据整理的系统和方法。 例如，物理数据可以是能量基础设施传感器数据。 系统可以使用回归模型在数据丢失期间执行传感器数据的估计。 该系统可以通过比较使用回归模型估计的物理数据的概率分布函数和实际物理数据来评估回归模型的准确性。