مدل پیش‌بین تأثیر انرژی نهفته بر تغییرات فرهنگی در بهره‌برداری اجتماع مدارس سبز باتأکیدبر نقش تعدیل‌گر دیوار خارجی
الموضوعات :
سمیه دولت
1
,
فهیمه معتضدیان
2
,
غزال صفدریان
3
,
حیدر جهانبخش
4
1 - گروه معماری، واحد پردیس، دانشگاه آزاداسلامی، پردیس، ایران
2 - استادیار گروه معماری، واحد پردیس، دانشگاه آزاداسلامی، پردیس، ایران.
3 - استادیار گروه معماری، واحد پردیس، دانشگاه آزاداسلامی، پردیس، ایران
4 - دانشیار گروه معماری، واحد تهران، دانشگاه پیام‌نور، تهران، ایران.
الکلمات المفتاحية: تغییرات فرهنگی و اقلیمی, اجتماع کنونی, انرژی نهفته و انرژی بهره‌برداری, مطالعات اجتماعی, مدارس سبز, مدل پیش‌بین, هستۀ دیوار خارجی.,
ملخص المقالة :
ساختمان‌ها به‌دلیل مصرف منابع و انرژی، تأثیر قابل‌توجهی بر تغییرات فرهنگی و اقلیمی دارند، که از چالشهای اصلی بشر در اجتماع کنونی میباشد. انرژی در ساختمان دارای 2مؤلفۀ انرژی نهفته و انرژی بهره‌برداری میباشد. به‌طورخاص، دانشمندان در سرتاسرجهان برروی استراتژیهای کاهش مصرف انرژی ساختمان‌ها درحال مطالعه و بررسی هستند که بیشتر مطالعات اجتماعی درپی کاهش مصرف انرژی بهره‌برداری و یا انرژی نهفته به‌صورت مجزاء صورت گرفته است. لذا، شکافی ازمنظر عدم‌توجه مطالعات اجتماعی به تأثیر انرژی نهفته ساخت‌مایه برروی انرژی بهره‌برداری ساختمان‌ها دیده میشود. همچنین مطالعات انرژی کمتر برروی ساختمانهای آموزشی با رویکرد اجتماعی صورت گرفتهاند. شکافهای موجود هدف‌اصلی پژوهش حاضر را تدوین و آزمون مدل پیش‌بین از تأثیرگذاری انرژی نهفته تغییرات فرهنگی برروی انرژی بهره‌برداری اجتماع ساختمانهای مدارس سبز قرار می‌دهد و بهدنبال نقش تعدیل‌کنندۀ انرژی نهفتۀ هستۀ دیوار خارجی در روابط علّی مدل مفهومی است. محقق با روش کمی و بهرهگیری از یک روششناسی سیستماتیک از تکنیکهای پیشرفته مدل‌سازی معادلات ساختاری واریانس محورجهت آزمون فرضیات پژوهش بهره برده است. تعداد 702نمونه پس‌از جمعآوری و غربالگری، با آزمون روایی، پایایی و برازش مدل بیرونی موردآزمون قرار گرفته و فرضیات در قالب مدل ساختاری آزمون گردیدند. نتایج R2 =0.704, 0.755 در 2معادلۀ ساختاری خبر از یک تبیین بسیار قدرتمند از واریانس یا رفتار متغیر بارسرمایشی و بارگرمایشی که همان انرژی بهره‌برداری میباشند، می‌دهد. به‌عبارتی مدل در مجموع بین 70تا75درصد از تأثیر رفتار انرژی نهفته بر انرژی بهره‌برداری را پیشبینی می‌کند.
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