Lendra, Lendra (2024) MODEL OPTIMALISASI ENERGI, EMISI DAN BIAYA PADA PROYEK KONSTRUKSI JALAN PERKERASAN LENTUR DAN PERKERASAN KAKU. Doctoral thesis, UNDIP.

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Abstract

The energy crisis and global climate change, linked to the world's increasing
energy consumption, threaten environmental and resource sustainability. The
International Energy Agency (IEA) notes the growth in global energy consumption,
especially in developing countries, and the significant impact on CO2 emissions, with
energy demand expected to rise 49% through 2040, making fossil fuel limitations and
CO2 impacts a serious concern. Projected economic and technological advances require
efforts to maintain energy sustainability. This research is based on three gaps: first,
there is a lack of integrated energy, emission and cost calculation models in road
construction design; second, there is no model that optimizes energy, emission and cost
by utilizing predicted International Roughness Index (IRI) values to determine the
timing and type of maintenance/rehabilitation; and third, pavement design policies do
not include Life Cycle Assessment (LCA) criteria.
This research aims to determine the factors that affect energy and emissions in
road construction projects, by developing energy and emission calculation methods
using the US EPA model based on Bina Marga's AHS productivity analysis, with
novelty building a prediction model of the International Roughness Index (IRI) value
using Artificial Neural Network (ANN) modeling to determine the timing of road
maintenance implementation, and integrating the IRI prediction model into the energy,
emission, and cost calculation methods as one of the considerations for choosing the
type of pavement.
The results showed that the factors affecting energy and emissions in road
construction projects are: equipment productivity, quantity of work, engine/equipment
power, brake specific fuel consumption, load factor, working hours/equipment
operation, project duration, and conversion factor from fuel to energy. The method of
calculating energy and emissions in road construction projects developed based on
productivity analysis and modification of the Bina Marga AHS by incorporating the
formula for calculating fuel consumption per hour using the US EPA method, which is
then converted to energy and emission units, can be used to calculate the amount of
energy, emissions, and costs within the limits of the cradle to cradle system. In this
study, it has been found that the use of VDF load equivalent factor 5 actual load to
predict the IRI value of flexible pavement is more accurate. The ANN model with 6-8-
16-1 configuration produced results with R = 0.8550, R2 = 0.7288, RMSE = 0.2211, and
MAPE = 0.0437. In addition, the results of this study also state that the VDF load
equivalent factor 4 actual load is more accurate in predicting the IRI value of rigid
pavement. The ANN model with 6-28-1 configuration produced results with R =
0.8094, R2 = 0.6095, RMSE = 0.294, and MAPE = 0.0469. Innovation by integrating
the IRI value prediction model into the energy, emission, and cost calculation method
can be done to produce a calculation simulation in one cycle over the life of the plan
(cradle to cradle) from the initial, operational and recurring (O&R) and
decommissioning stages to determine the most optimal alternative based on road needs,
where the optimization results show a preference for rigid pavement in terms of energy
and investment costs, while flexible pavement is superior in terms of emissions.
Keywords: ANN, energy, IRI, optimization, flexible pavement, rigid pavement.

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