INTERIOR MOULD GROWTH RISK REDUCTION: APPLICATION OF NONLINEAR PROGRAMMING FOR ENVELOPE OPTIMIZATION



Similar documents
MULTI-WORKDAY ERGONOMIC WORKFORCE SCHEDULING WITH DAYS OFF

Pedro M. Castro Iiro Harjunkoski Ignacio E. Grossmann. Lisbon, Portugal Ladenburg, Germany Pittsburgh, USA

Capacity Planning. Operations Planning

RESOLUTION OF THE LINEAR FRACTIONAL GOAL PROGRAMMING PROBLEM


Cooperative Distributed Scheduling for Storage Devices in Microgrids using Dynamic KKT Multipliers and Consensus Networks

arxiv: v1 [cs.sy] 22 Jul 2014


Lecture 13: Martingales

Photovoltaic Power Control Using MPPT and Boost Converter

A Hybrid AANN-KPCA Approach to Sensor Data Validation

ACE-1/onearm #show service-policy client-vips

Mobile Broadband Rollout Business Case: Risk Analyses of the Forecast Uncertainties

Market-Clearing Electricity Prices and Energy Uplift

Optimal Taxation. 1 Warm-Up: The Neoclassical Growth Model with Endogenous Labour Supply. β t u (c t, L t ) max. t=0

cooking trajectory boiling water B (t) microwave time t (mins)

HEURISTIC ALGORITHM FOR SINGLE RESOURCE CONSTRAINED PROJECT SCHEDULING PROBLEM BASED ON THE DYNAMIC PROGRAMMING

Levy-Grant-Schemes in Vocational Education

HR DEPARTMENTAL SUFFIX & ORGANIZATION CODES

Spline. Computer Graphics. B-splines. B-Splines (for basis splines) Generating a curve. Basis Functions. Lecture 14 Curves and Surfaces II

DC-DC Boost Converter with Constant Output Voltage for Grid Connected Photovoltaic Application System

USE OF EDUCATION TECHNOLOGY IN ENGLISH CLASSES

Georgia State University CIS 8000 IT Project Management. Upon completion of the course, students should be able to:


SELECTIVE GLAZING FOR SUN CONTROL

Forecasting Sales: A Model and Some Evidence from the Retail Industry. Russell Lundholm Sarah McVay Taylor Randall

HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD

Automated Price and Demand Response Demonstration for Large Customers in New York City using OpenADR

Stochastic Optimal Control Problem for Life Insurance

東 海 大 學 資 訊 工 程 研 究 所 碩 士 論 文


Genetic Algorithm with Range Selection Mechanism for Dynamic Multiservice Load Balancing in Cloud-Based Multimedia System

A = p 4 (0.05)2 = (10-3 ) m 2. J = p 2 (0.025)4 = (10-4 ) m 4. s = P A = 2(10 3 ) (10-3 = MPa. t = Tc J = 500(0.

BIG LOTS STORES INC. IMPLEMENTATION SPECIFICATIONS ASC X12 INVOICE TRANSACTION SET 810 VERSION 5010

Education's Purpose. Faculty

Event Based Project Scheduling Using Optimized Ant Colony Algorithm Vidya Sagar Ponnam #1, Dr.N.Geethanjali #2

A Reverse Logistics Model for the Distribution of Waste/By-products. Hamid Pourmohammadi, Maged Dessouky*, and Mansour Rahimi

Application of Fast Response Dual-Colour Pyroelectric Detectors with Integrated Op Amp in a Low Power NDIR Gas Monitor

Q-SAC: Toward QoS Optimized Service Automatic Composition *

Voltage level shifting

The Application of Multi Shifts and Break Windows in Employees Scheduling

Analysis of intelligent road network, paradigm shift and new applications

A robust optimisation approach to project scheduling and resource allocation. Elodie Adida* and Pradnya Joshi

1. Oblast rozvoj spolků a SU UK 1.1. Zvyšování kvalifikace Školení Zapojení do projektů Poradenství 1.2. Financování

Master degree studies, basic curriculum


Put the human back in Human Resources.

Optimization of Nurse Scheduling Problem with a Two-Stage Mathematical Programming Model

1.- L a m e j o r o p c ió n e s c l o na r e l d i s co ( s e e x p li c a r á d es p u é s ).

Vom Prototyp zum MVP. Peter Spisak Senior Lead Architect Online and VAS Development. Public Nicht vertraulich

Software Project Management tools: A Comparative Analysis

1. Degenerate Pressure


11/6/2013. Chapter 14: Dynamic AD-AS. Introduction. Introduction. Keeping track of time. The model s elements

ESIGN Rendering Service

The Prediction Algorithm Based on Fuzzy Logic Using Time Series Data Mining Method

MODEL-BASED APPROACH TO CHARACTERIZATION OF DIFFUSION PROCESSES VIA DISTRIBUTED CONTROL OF ACTUATED SENSOR NETWORKS

< IGBT MODULES > CM400DY-34A HIGH POWER SWITCHING USE INSULATED TYPE APPLICATION

Silicon Diffused Power Transistor

Internet Engineering. Jacek Mazurkiewicz, PhD Softcomputing. Part 1: Introduction, Elementary ANNs


Improvement in Forecasting Accuracy Using the Hybrid Model of ARFIMA and Feed Forward Neural Network

UNIFICATION OF OVERHEAD LINES IN THE CONDITIONS OF THE MARKET OF TWO-PARTY AGREEMENTS AND BALANCING ELECTRIC ENERGY MARKET

Optimal Stock Selling/Buying Strategy with reference to the Ultimate Average

Campus Sustainability Assessment and Related Literature

Optimal Testing Resource Allocation, and Sensitivity Analysis in Software Development

Strategic Optimization of a Transportation Distribution Network

Your Logo Here Creative Ways to Finance Your Working Capital Needs. February 22, /24/2012

I n la n d N a v ig a t io n a co n t r ib u t io n t o eco n o m y su st a i n a b i l i t y

Universal systems for frameless doors

A Hybrid Method for Forecasting Stock Market Trend Using Soft-Thresholding De-noise Model and SVM

DSL LINE ISOLATION TRANSFORMERS THRU HOLE OR SMD Parts are UL1950 & CSA-950 Recognized Under UL File# E or are Pending

DETC A SYSTEMATIC METHODOLOGY FOR ACCURATE DESIGN-STAGE ESTIMATION OF ENERGY CONSUMPTION FOR INJECTION MOLDED PARTS

Simultaneous Perturbation Stochastic Approximation in Decentralized Load Balancing Problem

E190Q Lecture 5 Autonomous Robot Navigation

The All New... TACO ZONE CONTROLS WIRING GUIDE

Digital Product Definition Data Practices

A Background Layer Model for Object Tracking through Occlusion

Understanding Potential Induced Degradation

The Virtual Machine Resource Allocation based on Service Features in Cloud Computing Environment

CO2 Emissions. Indirect CO 2. Emissions Electricity and Heat Production 25 % Direct Emissions AFOLU 24 % Energy 1,4% Buildings 6,4 % Industry 11 %

SOFTLINK 300. CPU Specifications. Reference Manual

Estimating Time-Varying Equity Risk Premium The Japanese Stock Market

Identify and ranking the factors that influence establishment of total quality management system in Payame Noor University of Lordegan

Journal Of Business & Economics Research September 2005 Volume 3, Number 9

Water-Bee Smart Irrigation System DA

BRICK LED Design Ronni Gol

Transcription:

INERIOR MOULD GROWH RISK REDUCION: APPLICAION OF NONLINEAR PROGRAMMING FOR ENVELOPE OPIMIZAION Nuno M. M. Ramos Isabel M. Rbero João M.P.Q. Delgado Vasco Pexoo de Freas eresa Eseves FACULY OF ENGINEERING UNIVERSIY OF PORO LABORAORY OF BUILDING PHYSICS N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-1

PRESENAION INRODUCION CASE SUDY SIMULAION OPIMIZAION PROGRAMME RESULS CONCLUSION N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-2

INRODUCION N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-3

INRODUCION N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-4

CASE SUDY N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-5

CASE SUDY 27 m 3.6 m 7.15 m N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-6

CASE SUDY 27 m 7.15 m N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-7

CASE SUDY Eas 2.6 (5.6x1.85) (1.1) (2.7x1.85) (6.3x1.85) (1.9x1.85)(0.9)(1.1) (5.6x1.85) N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-8

CASE SUDY buldng elemens N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-9

CASE SUDY oudoor emperaure N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-10

CASE SUDY venlaon 30 m 3 /h.person N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-11

CASE SUDY Objecves + s > dp Concree Concree + Insulaon Ex. In. Ex. In. N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-12

SIMULAION ENERGY PLUS hea balance z sl Q 1 N surperfíc es h A 1 s N zonas mc p 1 C 11 z 6 N z superfíces mnfcp h A N 1 1 msyscp zonas mc p sup mnfc p C z 3 msysc p z 3 2 2 z 1 3 3 z hea ransfer C p x, novo, ango 1, novo, ango 1, novo, novo x x N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-13

SIMULAION Março 2011-14

SIMULAION Resuls N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-15

SIMULAION Resuls hckness (cm) 0 1 2 3 4 5 6 7 8 9 mn 0.4 1.6 2.3 2.9 3.3 3.7 4.0 4.2 4.4 4.6 máx 30.7 33.1 34.6 35.5 36.3 36.8 37.3 37.6 37.9 38.1 5% 7.5 8.8 9.7 10.2 10.6 10.9 11.2 11.4 11.6 11.7 Year méd 15.8 17.5 18.5 19.2 19.7 20.1 20.4 20.6 20.8 21.0 Days wh surface condensaon on walls Days wh surface condensaon on celng 95% 23.6 26.0 27.4 28.3 29.0 29.5 29.9 30.3 30.6 30.8 33 12 4 2 1 1 1 1 1 0 29 Dec 126 22 4 4 1 1 1 1 1 0 N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-16

SIMULAION Average ar emperaure n January N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-17

OPIMIZAION PROGRAMME Mnmze Resrcons NSB 2011-18 N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves Ns N j wn U j Np ns ns p C A C x A 1 1 A RD x x h x C Np íns s z íns s con ns s s ns ns p ns 1 2 h U x x C sj z j sj glass j sj sj glas j glas p glas 0.17 1 2 C m A h C C C m A h p k Ns k k z z z z z p sk k Ns k k sl z Q nf 1 3 2 nf 1 1 6 11 3 1 2 3 3 x x x x C con s con ns con ns con con con ns con con p con 2 dp s

OPIMIZAION Mnmze subjec o: z = c x + d y f(x) + A 1 y b 1 A 2 x + A 3 y b 2 l1 x u1, l2 y u2 f.o. lnear K nonlnear feasble regon y Opmal soluon K x z = 0 decreasng drecon of z N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-19

OPIMIZAION CASE SUDY Problem wh Nonlnear Consrans Sofware GAMS/MINOS Projec Lagrangan Algorhm N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-20

OPIMIZAION CASE SUDY JANUARY SELECED DAYS N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-21

RESULS Indoor emperaure January 4 emperaure (ºC) 18 15 12 9 6 3 1:00 4:00 7:00 10:00 13:00 16:00 19:00 22:00 1:00 me (h) (a) e no nsulaon, U=6 (EP) nsulaon 4.5cm, U=6 (EP) nsulaon 4.5cm, U=6 (OP) N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-22

RESULS Surface condensaon January 4 emperaure (ºC) 18 15 12 9 6 3 1:00 4:00 7:00 10:00 13:00 16:00 19:00 22:00 1:00 me (h) (b) po s no nsulaon (EP) s wh 4.5cm (EP) s wh 4.5cm (OP) N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-23

RESULS Smulaon January 25 emperaure (ºC) 25 20 15 10 5 no nsulaon, U=6 (EP) nsulaon 3cm U=6 (EP) nsulaon 3cm U=6 (OP) e (a) 0 1:00 4:00 7:00 10:00 13:00 16:00 19:00 22:00 1:00 me (h) N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-24

RESULS Smulaon December 29 15 12 emperaure (ºC) 9 6 3 0 dp s whou XPS (E.P.) s whou XPS (O.P.) 3:00 5:00 7:00 9:00 11:00 13:00 15:00 17:00 19:00 21:00 23:00 1:00 3:00 me (h) N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-25

CONCLUSIONS Smulaon Dealed npus Dealed resuls Opmzaon derved from full analyss repeon Opmzaon programme Smulaon merged n opmzaon process Smplfed model wh smpler npus Easy o use wh accepable resuls N.M.M. Ramos / I.M. Rbero /J.M.P.Q. Delgado / V.P. de Freas /. Eseves NSB 2011-26