60 research outputs found
Water–Phosphorus Nexus for Wet-Process Phosphoric Acid Production
The water–phosphorus nexus
problem for wet-process phosphoric
acid production is first addressed in this article. A systematic methodology
for water system optimization and water–phosphorus nexus analysis
is proposed. On the basis of the preliminary process flowsheet and
water flow rate balance, the potential water sources and sinks as
well as the key component can be extracted. The mathematical model
for the water system optimization integrated with water flow rate
balance is presented. The process flowsheet can be improved according
to the optimized water system. The flow rate of fresh water is reduced
from 1803.98 t/h (preliminary design) to 160.98 t/h (improved design).
The utilization efficiencies of the phosphorus element (calculated
as P<sub>2</sub>O<sub>5</sub>) are calculated for the preliminary
and improved designs. Because the process for wet-process phosphoric
acid production is mostly in the aqueous phase, the utilization efficiency
of the phosphorus element is increased from 94.22% (preliminary design)
to 98.76% (improved design) due to the reuse and recycling of water
stream with the phosphorus element. Water minimization and phosphorus
recovery can be achieved simultaneously. The additional annualized
profit for the improved design reaches 248.8 × 10<sup>6</sup> CNY/a, which is a great benefit for the production plant
Deciphering Refinery Water System Design and Optimization: Superstructure and Generalized Mathematical Model
The up-to-date approaches
to optimizing water systems only include
fresh water, regenerated water and wastewater and ignore other types
of water in refinery, i.e., desalted water, deaerated water, circulated
cooling water, steam with different pressure levels and condensate
water. Therefore, the existing mathematical model for water system
optimizaiton is not directly applicable for the optimization of practical
refinery water systems. To overcome the limitation and bridge the
theory and application, we first presented a generalized model of
water-using processes including multiple types of water and a general
superstructure for the optimization of refinery water system. The
superstructure consists of water-using processes including multiple
types of water in the main production units (i.e., crude oil distillation,
fluid catalytic cracking), water pretreatment systems (i.e., fresh
water station, desalted water station, steam power station) and wastewater
treatment system. The flow rate balance equations for those components
of a refinery water system and the correlation for all types of water
are formulated. The replacement ratio of altered type of water is
introduced in the flow rate balance equations for water reuse/recycling
and it avoids the imprecise data extraction of limiting water quality
for the inlets of water-using processes. We presented two mathematical
models with different objective functions (minimum flow rate of water
resource (Scenario 1) and minimum partial annualized cost (Scenario
2)). The proposed models are applied for the optimization of the water
system of a large-scale refinery in China. Results show that the water
system with a minimum flow rate of water source can be obtained in
Scenario 1. In Scenario 2, the profit of water conversation for five
strategies cannot offset the investment cost of added pipelines, and
their actual replacement ratios are zero. It leads to an economic
and simpler water system with slightly higher flow rate of water resources
Algebraic Approach for the Integration of the Hydrogen Network with a Single Impurity
Fresh
hydrogen is an expensive utility in refineries. The integration
of hydrogen networks can make full use of hydrogen and reduce the
fresh hydrogen consumption. In this work, a rigorous algebraic approach
is proposed on the basis of the pinch conception to identify the minimum
fresh hydrogen consumptions and pinch locations of hydrogen networks.
This algebraic approach is derived from an existing graphical method
by transforming the moving procedure of the source composite curve
into an algebraic calculation according to the geometrical transformations.
The conception of relative flow rate is introduced to describe each
hydrogen source and sink. On this basis, a noniterative algebraic
procedure is developed to figure out the surplus fresh hydrogen in
each interval. Finally, the minimum fresh hydrogen consumption and
pinch location can be identified. Furthermore, the proposed approach
can be enlarged by considering the hydrogen purification process,
and the purification process can be further analyzed to minimize its
feed flow rate. This approach has a clear conception and an easy procedure
and is valid for the hydrogen network with fresh hydrogen of any hydrogen
concentration. A conventional hydrogen network is analyzed to test
the applicability of the proposed approach
Coefficients of the polynomial fit for <i>n</i>, <i>Q</i>, <i>α</i>, and ln <i>A</i>.
<p>Coefficients of the polynomial fit for <i>n</i>, <i>Q</i>, <i>α</i>, and ln <i>A</i>.</p
4th order polynomial fit of the material constants.
<p>(a) <i>α</i>, (b) <i>n</i>, (c) <i>Q</i>, and (d) ln <i>A</i>.</p
Chemical composition of the 316LN steel used in this study (wt.%).
<p>Chemical composition of the 316LN steel used in this study (wt.%).</p
The relative error between the predicted curve and experimental curve at 900°C and 10 s<sup>−1</sup> and the given strain.
<p>The relative error between the predicted curve and experimental curve at 900°C and 10 s<sup>−1</sup> and the given strain.</p
Linear regression fits of (a) ln <i>σ</i>-ln and (b) <i>σ</i>-ln data.
<p>(Selected data.)</p
Comparison of experimental curves and predicted curves at various strain rates.
<p>(a) 10<sup>−3</sup> s<sup>−1</sup>, (b) 10<sup>−2</sup> s<sup>−1</sup>, (b) 10<sup>−1</sup> s<sup>−1</sup>, (b) 1 s<sup>−1</sup> and (b) 10 s<sup>−1</sup>.</p
Flow stress curves of 316LN steels compressed at different temperatures and strain rates.
<p>(a) 10<sup>−3</sup> s<sup>−1</sup>, (b) 10<sup>−2</sup> s<sup>−1</sup>, (b) 10<sup>−1</sup> s<sup>−1</sup>, (b) 1 s<sup>−1</sup> and (b) 10 s<sup>−1</sup>.</p
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