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Penyenggaraan merupakan aktiviti yang sangat penting bagi mengekalkan nilai aset bangunan sekolah, di samping menyediakan persekitaran yang kondusif bagi tujuan pengajaran dan pembelajaran. Bagi melaksanakan aktiviti penyenggaraan bangunan, pemeriksaan terhadap keadaan semasa bangunan adalah perlu. Ini bertujuan untuk mendapatkan maklumat mengenai kondisi bangunan dan penilaian yang bersistematik dapat dilaksanakan. Kertas ini membincangkan kajan terhadap keadaan bangunan sekolah rendah di bahagian Kuching, Sarawak yang telah dilaksanakan dengan menggunakan Matriks Condition Survey Protocol (CSP)1 sebagai alat pengukur. Selain itu, kajian ini juga bertujuan menilai perkaitan antara usia sekolah dengan bilangan kerosakan bangunan, markah keseluruhan dan pengkadaran bagi setiap sekolah Tiga perkara utama dikenalpasti melalui analisis Matriks CSP1 iaitu bilangan keseluruhan kerosakan bangunan, markah keseluruhan kerosakan bangunan dan pengkadaran keseluruhan bagi setiap sekolah. Analisis yang dijalankan terhadap 24 buah sekolah mendapati terdapat 4,725 kerosakan keseluruhan bangunan sekolah, markah keseluruhan yang diperolehi adalah 45,868 manakala pengkadaran keseluruhan bagi semua sekolah adalah 9.71, iaitu berada pada tahap yang sederhana teruk. Hasil kajian mendapati ketiga-tiga aspek tersebut adalah berkaitan dengan usia sekolah. Ini menyokong teori bahawa semakin tinggi usia sekolah, semakin banyak kerosakan bangunan yang berlaku.

The air-spray patterns of high solid coatings were examined using a Particle Image Velocimeter (PIV) to determine the affects of varying the composition (oligomeric acrylic, oligomeric ester, and melamine resin) and molecular weight of high solid resins in coating formulations on their sprayability. High molecular weight tails (e.g., in the acrylic) are known to increase the elasticity of the fluid, and their presence imparted poor spray behavior (i.e., less misting, presence of ligaments, narrower exit fanning, and higher velocities farther from the nozzle) to the high solid coating. The Sauter Mean Diameter (SMD) of the droplets increased with increasing viscosity, which is dependent on weight average molecular weight of the total components of the blends. High solids stored at 60°C resulted in poorer spray with both increasing storage time and increasing levels of catalyst stored for 2 h. The high solid coatings were Newtonian fluids with no elastic functions associated with shear deformations. The elastic behavior associated with the high molecular weight tails in the acrylic oligomers is related, through their similar variation in spray behavior with HEUR thickened latex coatings in Part IV of this series, to dynamic uniaxial extensional viscosities.

In this study, the focus is on the spray behavior of latex coatings thickened with structurally different surfactant-modified, water-soluble polymers (associative thickeners of the hydrophobically modified, ethoxylated urethane [HEUR] type). Particle image velocimetry (PIV) profiles are considered in the perspective of the dynamic uniaxial extensional viscosity (DUEV) of the coatings and an effort to understand the results in terms of the structural aspects of the thickener molecules is undertaken. A high-M v hydroxyethyl cellulose (HEC) thickened formulation, with a significant DUEV, does not atomize well. Among the HEUR thickeners, the addition of larger hydrophobes in the terminal positions requires less thickener to achieve a 90 KU viscosity and produces lower DUEVs and lower viscosities at high-shear rates. This is necessary to produce formulations with acceptable spray characteristics (i.e., good atomization). The sprayability of these systems is reflected in their velocity profiles and particle size/particle size distributions. Poorer spray characteristics are reflected in ligaments and broad particles size distributions. This study highlights the ability to control the particle size/size distribution and velocity profiles of coatings formulations through the use of structurally different HEUR associative thickeners. Variations in sprayability among different nozzle geometries are also studied.

Oxyethylene (PEO)/oxypropylene (PPO) triblock polymers are added to colorant formulations to determine the influence of molecular weight and other structural variances on the rheology and color development of tinted latex paints. Waterborne coatings are a matrix of many coating components. In this study, a 108- or a 600-nm latex was thickened with a nonassociative thickener, hydroxyethyl cellulose, or an associative telechelic HEUR thickener. Triblock polymers with internal PPO segments and PEO terminal segments added as a dispersant to colorant packages, lead to better color development than PPO/PEO/PPO triblocks dispersants in carbon black (CB) tinted paints. The increase in color development with high molecular weight (MW) triblocks starts at a very low concentration (2 mM) and plateaus in a Langmuir-type adsorption isotherm. Lower molecular weight triblock polymers also exhibit this behavior in CB-, red-, and yellow-tinted latex coatings; however, increasing the terminal PEO segment sizes leads to better color development only in the CB-tinted coatings. With large PEO terminal units red and yellow tints are high only at very low concentrations (2 mM) of the triblock. This parabolic response in color development, in contrast to CB-tinted formulations, is attributed to the high surface area and porosity of CB that limits the amount of large PEO segments interacting with the talc particle present at twice the volume fraction of the colorant. With the lower surface areas of the red and yellow colorants, the interaction of the large PEO terminal segments with talc particles accounts for the limited triblock concentration for which good color development is observed. This can be reversed by decreasing or eliminating talc from the formulation.

A matrix of coating variables, nonassociative versus associative thickeners, different latex median particle sizes, individual surfactants and colorants [carbon black (CB), red, and yellow pigments], was examined for their influence on variances in coatings rheology and color development. Within the different coating groups, the variable of interest in this study was the surfactant added to the colorant formulation. In all three colorant formulations, sodium dodecyl sulfate (an anionic surfactant) provided poorer color development (CD) than in applied formulations containing an equivalent nonylphenol oxyethylene (EO) surfactant. In CB formulations, nonionic surfactants with higher EO content provide improved color development at low (2 mM) concentrations, but near equality in CD is achieved with low EO surfactants at higher concentrations. In contrast to CB formulations, red and yellow colorants exhibit good color development with high EO content nonionic surfactants only at low nonionic surfactants concentrations. This variance appears to be related to the interactions of surfactants with inorganic pigments (talc and laponite) in the colorant formulation.

For almost two decades, it has been known that the addition of colorants to a waterborne latex coating thicknened with an associative thickener will result in a viscosity loss. The influence of surfactants on viscosity variations in waterborne latex coatings, as discussed in our most recent JCTCoatingsTech article,1 is the source of the viscosity decreases. To evaluate this problem, aqueous solutions containing large quantities of five different surfactants, and the smallest particle size of the colorants, carbon black (CB), were prepared. Large quantities of surfactant were used to allow for adsorption on, and stabilization of, CB. When traditional associative polymers (HMHEC, HASE, and a telechelic HEUR) were used to thicken carbon black dispersions, viscosity decreases were not observed, for most of the surfactnat is adsorbed on the CB’s surface. There is enough surfactant, however, to promote viscosity decreases in comb-HEUR thickened CB dispersions. Moving beyond the colorant dispersions, the CB, yellow, or red colorants were then added to a commercial latex paint that contains many surfactants, glycol ether, and coalescing aids, and significant viscosity decreases were observed. The decreases were very dramatic as the colorant concentration was increased to obtain deeper color tones, due to the additional excess surfactant added to the coating. Reduction in total surfactant levels in the colorant was an obvious solution, but this led to rub-up incompatibility. The conflict between viscosity retention and rub-up incompatibility was resolved when the surfactant concentration was reduced by adding to the colorant formulation compositionally different hydrophobically-modified poly(oxyethylenes) and hydrophobe-modified maleic acid co-oligomers.

Surfactants, varying in their chemical composition and hydrophobic behavior, are used in the formulation of a waterborne coating. These differences influence their aggregation in micellar structures, their interaction with associative thickeners, and in particular, the synergies present in their competitive adsorptions on the disperse phases in a waterborne coating. Adsorption of HEUR thickeners on latexes and the ability of surfactants to displace them from those surfaces is an important variable in the dispersion’s viscosity. With large particle latexes, viscosity increases arise primarily from the network built through the interaction of HEURs with surfactants in the aqueous phase. Fluorescence is used to verify the mechanism by which surfactants enhance associative thickener viscosities. That is best achieved with nonionic surfactants, because of their synergies with large hydrophobe HEURs at low concentration. With decreasing latex particle size the adsorbed species is an important contributor to the dispersion’s viscosity through its contribution to the latex’s effective volume fraction increase and when the size of the adsorbed HEUR is matched to the separation distances of the latex at 0.25 volume fraction. Achieving controlled shear-thinning behavior in small particle size latex paints with the economic constraints on the amount of HEUR required to obtain 90 KU viscosities are discussed.

Building condition assessment is a critical activity in Malaysia-s Comprehensive Asset Management Model. It is closely related to building performance that impact user-s life and decision making. This study focuses on public primary school, one of the most valuable assets for the country. The assessment was carried out based on CSP1 Matrix in Kuching Division of Sarawak, Malaysia. Based on the matrix used, three main criteria of the buildings has successfully evaluate: the number of defects; schools rating; and total schools rating. The analysis carried out on 24 schools found that the overall 4, 725 defects has been identified. Meanwhile, the overall score obtained was 45, 868 and the overall rating is 9.71, which is at the fair condition. This result has been associated with building age to evaluate its impacts on school buildings condition. The findings proved that building condition is closely related to building age and its support the theory that 'the ageing building has more defect than the new one'., {"references":["Syamilah Yacob. 2005. Maintenance Management System through\nStrategic Planning for Public School in Malaysia. Sarjana Sains\n(Pengurusan Pembinaan). Universiti Teknologi Malaysia.","Nik Elyna Myeda, Syahrul Nizam Kamaruzzaman & Pitt, M. 2011.\nMeasuring the performance of office buildings maintenance\nmanagement in Malaysia. Journal of Facilities Management. Vol 9 No.\n3. pp. 181-199.","Abdul Lateef, O. A., Mohd Faris Khamidi & Arazi Idrus. 2011.\nAppraisal of the building maintenance management practices of\nMalaysian universities. Journal of Building Appraisal. Vol 6, . Pp\n261-275.","Edwards, M. 1992. Building Condition, Parental Involvement and\nStudent Achievement in the D.C. Public School System. M. Ed.\nDissertation. Washington, D.C., Georgetown University.","Lewis, M. 2001. Facility conditions and students test performance in the\nMilwaukee Public School. Council of Educational Facility Planner,\nInternational, Scottsdale, AZ.","Earthman, G.I. 2002. School Facility Conditions and Student Academic\nAchievement. UCLA-s Institute for Democracy, Education, &\nAccess. University of California, Los Angeles.","Earthman, G.I. 2002. School Facility Conditions and Student Academic\nAchievement. UCLA-s Institute for Democracy, Education, &\nAccess. University of California, Los Angeles.","Hutchinson, L. 2003. Educational environment. British Medical Journal.\nVol. 326. Pp 810-812.","Mendell, M.J., Heath, G.A. 2003. Do Indoor Environments in Schools\nInfluence Student Performance? A Review of the Literature. Indoor\nHealth and Productivity Project (IHP). USA.\n[10] Bosch, S.J. 2004. Identifying relevant variables for understanding how\nschool facilities affect educational outcomes. Tesis doktor falsafah.\nTidak diterbitkan. Georgia Institute of Technology.\n[11] Tiburcio, T. & Finch, E.F. 2004. The impact of an intelligent classroom\non pupils- interactive behavior. Facilities. 23(5/6): 262-278.\n[12] Adeogun, A.A. & Osifila, G.I. 2008. Relationship between Educational\nResources and Students- Academic Performance in Lagos State\nNigeria. International Journal of Educational Management. Vol 5&6.\npp. 144-153.\n[13] Tanner, C.K. 2008. Effect of school design on students outcomes.\nJournal of Educational Administration. 47(3): 381-399.\n[14] Uline, C. & Tschannen-Moran, M. 2008. The wall speak: the interplay\nof quality facilities, school climate, and student achievement. Journal\nof Education Administration. Vol 46. No 1. pp. 56-73.\n[15] Fram, S.M. 2010. One built environment: an example for school\nadministrators and planners. Journal of Educational Administration.\nVol. 48. No. 4 pp 468-489.\n[16] Nurul Syakima, M.Y., Maimunah Sapri, Mohd Shahril A.R. 2011.\nMeasuring Performance for Classroom Facilities. 2011 International\nConference on Sociality and Economics Development IPEDR. Vol.10.\nIACSIT Press, Singapore.\n[17] Rapoport, A. 1982. The Meaning of the Built Environment: A Nonverbal\nCommunication Approach. Sage. Beverly Hill. USA.\n[18] Schneider, M. 2002. Do School Facilities Affect Academic Outcomes?\nNational Clearinghouse for Educational Facilities. Washington D.C.\n[19] GAO. 2011. Opportunities to Reduce Potential Duplication in\nGovernment Programs, Save Tax Dollars, and Enhance Revenue.\nReport to Congressional Addressees. United States Government\nAccountability Office. Mac 2011.\n[20] Ministry of Education (MOE). 2010. Number of School Statistic.\nWebsite: MOE. Access: 22 Aug 2010. Last update: 20 Aug 2010.\n[21] Che-Ani A.I., Tazilan A.S.M., Kosman K.A. 2011. The Development of\na Condition Survey Protocol Matrix.Structural Survey. 29(1):35-45."]}

Building inspection is one of the key components of building maintenance. The primary purpose of performing a building inspection is to evaluate the building-s condition. Without inspection, it is difficult to determine a built asset-s current condition, so failure to inspect can contribute to the asset-s future failure. Traditionally, a longhand survey description has been widely used for property condition reports. Surveys that employ ratings instead of descriptions are gaining wide acceptance in the industry because they cater to the need for numerical analysis output. These kinds of surveys are also in keeping with the new RICS HomeBuyer Report 2009. In this paper, we propose a new assessment method, derived from the current rating systems, for assessing the specifically smart school building-s condition and rating the seriousness of each defect identified. These two assessment criteria are then multiplied to find the building-s score, which we called the Condition Survey Protocol (CSP) 1 Matrix. Instead of a longhand description of a building-s defects, this matrix requires concise explanations about the defects identified, thus saving on-site time during a smart school building inspection. The full score is used to give the building an overall rating: Good, Fair or Dilapidated., {"references":["Mat-Deris, M.S., Malaysian Total Asset Management Approach, in Building Surveyors Role in Public Work Department (JKR) Seminar, JKR, Editor. 2009, Jabatan Kerja Raya: Jalan Sultan Salahudin, Kuala\nLumpur.","RICS, 3rd Edition Practice Notes, in R.P.G.o.t.R.I.o.C.S. (RICS), Editor.\n2009, RICS HomeBuyer Service: Coventry, United Kingdom.","Yacob, S., Maintenance Management System through Strategic Planning\nfor Public School in Malaysia, in Construction Management. 2005, Universiti Teknologi Malaysia: Johor.","Hoxley, M., Condition Inspections of Residential Property: A Procedural\nFramework. Journal of Structural Survey, 2002. 20(1): p. 31-35.","Hegazy, T., Ahluwalia, S.S. & Attalla, M., Two condition indicators for\nbuilding components based on reactive-maintenance data. Journal of Facilities Management, 2010. 8(1): p. 64-74.","Pitt, T.J., Data Requirements For The Prioritization of Predictive\nBuilding Maintenance. Journal of Facilities Management, 1997. 15(3/4):p. 97-104.","Alani, A.M.P., A. K.; Chapman, K. G. , Applications of The Developed\nQuantitative Model In Building Repair and Maintenance - Case Study. Journal of Facilities, 2001. 19(5/6): p. 215-221.","Che-Ani, A.I.R., A.; Zain, M.F.M; Tawil, N.M.; Hashim, A.E., Assessing The Condition of Traditional Khmer Timber Houses In\nCambodia - A Priority Ranking Approach. Journal of Building Appraisal, 2008. 4(2 ): p. 87-102.","Che-Ani, A.I.Z., A.I.; Zain, M.F.M; Tawil, N.M; Surat, M. Timber Defects in Building: A Study of Telapak Naning, Malacca, Malaysia. in\nWSEAS Transactions on Environment and Development. 2009:\nWSEAS.\n[10] Che-Ani, A.I.Z., A.; Md-Darus, Z.; Tawil, N.M. The Formulation of\nEvaluating Timber Defects As A Tool For Building Survey. in\nInternatioal Conference on Cultural Heritage & Tourism (CUHT) 2008.\n2008. Heraklion, Crete Island, Greece.\n[11] Mahmood, N. Building Surveyors in Private Sector - Condition Assessment. in Malaysia Building Surveyors Jamboree 2009. 2009. University Science Malaysia (USM)."]}

In providing a conducive learning environment for the student, the school building must be in good condition. This paper is evaluating the existing condition of primary school building in Sarawak, Malaysia. It focuses on building defects pattern for school building. The primary data collection is from the school building condition survey with involvement of 24 primary schools. The schools have been selected using simple random sampling and stratified sampling (of school age as the variable of selection). The reporting method is based on Condition Survey Protocol (CSP) 1 Matrix. Data analysis covers descriptive and inferential statistics. The analysis carried out found that the overall 4,725 defects have been identified. The building defect pattern is mainly on Ground Level of 3,176 defects, the highest number of defects components found on walls (798). 16.2% defects are cracks from 11 common defects and most of all the highest score of defects based on age of the building were the building in the range of 11 to 20 years.